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2024
- 1.Draude, C., Engert, S., Hess, T., Hirth, J., Horn, V., Kropf, J., Lamla, J., Stumme, G., Uhlmann, M., Zwingmann, N.: Verrechnung – Design – Kultivierung: Instrumentenkasten für die Gestaltung fairer Geschäftsmodelle durch Ko-Valuation, https://plattform-privatheit.de/p-prv-wAssets/Assets/Veroeffentlichungen_WhitePaper_PolicyPaper/whitepaper/WP_2024_FAIRDIENSTE_1.0.pdf, (2024). https://doi.org/10.24406/publica-2497.
@misc{claude2024verrechnung,
address = {Karlsruhe},
author = {Draude, Claude and Engert, Simon and Hess, Thomas and Hirth, Johannes and Horn, Viktoria and Kropf, Jonathan and Lamla, Jörn and Stumme, Gerd and Uhlmann, Markus and Zwingmann, Nina},
edition = 1,
editor = {Friedewald, Michael and Roßnagel, Alexander and Geminn, Christian and Karaboga, Murat},
howpublished = {White Paper},
keywords = {itegpub},
month = {03},
publisher = {Fraunhofer-Institut für System- und Innovationsforschung ISI},
series = {Plattform Privatheit},
title = {Verrechnung – Design – Kultivierung: Instrumentenkasten für die Gestaltung fairer Geschäftsmodelle durch Ko-Valuation},
year = 2024
}%0 Generic
%1 claude2024verrechnung
%A Draude, Claude
%A Engert, Simon
%A Hess, Thomas
%A Hirth, Johannes
%A Horn, Viktoria
%A Kropf, Jonathan
%A Lamla, Jörn
%A Stumme, Gerd
%A Uhlmann, Markus
%A Zwingmann, Nina
%B Plattform Privatheit
%C Karlsruhe
%D 2024
%E Friedewald, Michael
%E Roßnagel, Alexander
%E Geminn, Christian
%E Karaboga, Murat
%I Fraunhofer-Institut für System- und Innovationsforschung ISI
%R 10.24406/publica-2497
%T Verrechnung – Design – Kultivierung: Instrumentenkasten für die Gestaltung fairer Geschäftsmodelle durch Ko-Valuation
%U https://plattform-privatheit.de/p-prv-wAssets/Assets/Veroeffentlichungen_WhitePaper_PolicyPaper/whitepaper/WP_2024_FAIRDIENSTE_1.0.pdf
%7 1 - 1.Abdulla, M., Hirth, J., Stumme, G.: The Birkhoff Completion of Finite Lattices. In: Cabrera, I.P., Ferré, S., and Obiedkov, S. (eds.) Conceptual Knowledge Structures. pp. 20–35. Springer Nature Switzerland, Cham (2024).We introduce the Birkhoff completion as the smallest distributive lattice in which a given finite lattice can be embedded as semi-lattice. We discuss its relationship to implicational theories, in particular to R. Wille's simply-implicational theories. By an example, we show how the Birkhoff completion can be used as a tool for ordinal data science.
@inproceedings{10.1007/978-3-031-67868-4_2,
abstract = {We introduce the Birkhoff completion as the smallest distributive lattice in which a given finite lattice can be embedded as semi-lattice. We discuss its relationship to implicational theories, in particular to R. Wille's simply-implicational theories. By an example, we show how the Birkhoff completion can be used as a tool for ordinal data science.},
address = {Cham},
author = {Abdulla, Mohammad and Hirth, Johannes and Stumme, Gerd},
booktitle = {Conceptual Knowledge Structures},
editor = {Cabrera, Inma P. and Ferré, Sébastien and Obiedkov, Sergei},
keywords = {itegpub},
pages = {20--35},
publisher = {Springer Nature Switzerland},
title = {The Birkhoff Completion of Finite Lattices},
year = 2024
}%0 Conference Paper
%1 10.1007/978-3-031-67868-4_2
%A Abdulla, Mohammad
%A Hirth, Johannes
%A Stumme, Gerd
%B Conceptual Knowledge Structures
%C Cham
%D 2024
%E Cabrera, Inma P.
%E Ferré, Sébastien
%E Obiedkov, Sergei
%I Springer Nature Switzerland
%P 20--35
%T The Birkhoff Completion of Finite Lattices
%X We introduce the Birkhoff completion as the smallest distributive lattice in which a given finite lattice can be embedded as semi-lattice. We discuss its relationship to implicational theories, in particular to R. Wille's simply-implicational theories. By an example, we show how the Birkhoff completion can be used as a tool for ordinal data science.
%@ 978-3-031-67868-4 - 1.Hille, T., Stubbemann, M., Hanika, T.: Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research. Transactions on Machine Learning Research. (2024).
@article{hille2024reproducibility,
author = {Hille, Tobias and Stubbemann, Maximilian and Hanika, Tom},
journal = {Transactions on Machine Learning Research},
keywords = {itegpub},
note = {Reproducibility Certification},
title = {Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research.},
year = 2024
}%0 Journal Article
%1 hille2024reproducibility
%A Hille, Tobias
%A Stubbemann, Maximilian
%A Hanika, Tom
%D 2024
%J Transactions on Machine Learning Research
%T Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research.
%U https://openreview.net/forum?id=CtEGxIqtud - 1.Dürrschnabel, D., Priss, U.: Realizability of Rectangular Euler Diagrams, (2024).
@misc{dürrschnabel2024realizability,
author = {Dürrschnabel, Dominik and Priss, Uta},
keywords = {itegpub},
title = {Realizability of Rectangular Euler Diagrams},
year = 2024
}%0 Generic
%1 dürrschnabel2024realizability
%A Dürrschnabel, Dominik
%A Priss, Uta
%D 2024
%T Realizability of Rectangular Euler Diagrams - 1.Horn, V., Hirth, J., Holfeld, J., Behmenburg, J.H., Draude, C., Stumme, G.: Disclosing Diverse Perspectives of News Articles for Navigating between Online Journalism Content. In: Nordic Conference on Human-Computer Interaction. Association for Computing Machinery, Uppsala, Sweden (2024). https://doi.org/10.1145/3679318.3685414.Today, exposure to journalistic online content is predominantly controlled by news recommender systems, which often suggest content that matches user’s interests or is selected according to non-transparent recommendation criteria. To circumvent resulting trade-offs like polarisation or fragmentation whilst ensuring user’s autonomy, we explore how different perspectives within online news can be disclosed instead for guiding navigation. To do so, we developed an interactive prototype that displays article titles in correspondence to their argumentative orientation. In order to investigate how the usage of our novel navigation structure impacts the choice of news articles and user experience, we conducted an exploratory user study assessing the impact of the design parameters chosen. Implications are drawn from the study results and the development of the interactive prototype for the exposure to diversity in the context of navigating news content online.
@inproceedings{hci-lattice,
abstract = {Today, exposure to journalistic online content is predominantly controlled by news recommender systems, which often suggest content that matches user’s interests or is selected according to non-transparent recommendation criteria. To circumvent resulting trade-offs like polarisation or fragmentation whilst ensuring user’s autonomy, we explore how different perspectives within online news can be disclosed instead for guiding navigation. To do so, we developed an interactive prototype that displays article titles in correspondence to their argumentative orientation. In order to investigate how the usage of our novel navigation structure impacts the choice of news articles and user experience, we conducted an exploratory user study assessing the impact of the design parameters chosen. Implications are drawn from the study results and the development of the interactive prototype for the exposure to diversity in the context of navigating news content online.},
address = {New York, NY, USA},
author = {Horn, Viktoria and Hirth, Johannes and Holfeld, Julian and Behmenburg, Jens Hendrik and Draude, Claude and Stumme, Gerd},
booktitle = {Nordic Conference on Human-Computer Interaction},
keywords = {itegpub},
publisher = {Association for Computing Machinery},
series = {NordiCHI 2024},
title = {Disclosing Diverse Perspectives of News Articles for Navigating between Online Journalism Content},
year = 2024
}%0 Conference Paper
%1 hci-lattice
%A Horn, Viktoria
%A Hirth, Johannes
%A Holfeld, Julian
%A Behmenburg, Jens Hendrik
%A Draude, Claude
%A Stumme, Gerd
%B Nordic Conference on Human-Computer Interaction
%C New York, NY, USA
%D 2024
%I Association for Computing Machinery
%R 10.1145/3679318.3685414
%T Disclosing Diverse Perspectives of News Articles for Navigating between Online Journalism Content
%U https://doi.org/10.1145/3679318.3685414
%X Today, exposure to journalistic online content is predominantly controlled by news recommender systems, which often suggest content that matches user’s interests or is selected according to non-transparent recommendation criteria. To circumvent resulting trade-offs like polarisation or fragmentation whilst ensuring user’s autonomy, we explore how different perspectives within online news can be disclosed instead for guiding navigation. To do so, we developed an interactive prototype that displays article titles in correspondence to their argumentative orientation. In order to investigate how the usage of our novel navigation structure impacts the choice of news articles and user experience, we conducted an exploratory user study assessing the impact of the design parameters chosen. Implications are drawn from the study results and the development of the interactive prototype for the exposure to diversity in the context of navigating news content online.
%@ 9798400709661 - 1.Hirth, J., Hanika, T.: The Geometric Structure of Topic Models, (2024).Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an in-depth analysis of topic models is still an open research topic. State-of-the-art methods for interpreting topic models are based on simple visualizations, such as similarity matrices, top-term lists or embeddings, which are limited to a maximum of three dimensions. In this paper, we propose an incidence-geometric method for deriving an ordinal structure from flat topic models, such as non-negative matrix factorization. These enable the analysis of the topic model in a higher (order) dimension and the possibility of extracting conceptual relationships between several topics at once. Due to the use of conceptual scaling, our approach does not introduce any artificial topical relationships, such as artifacts of feature compression. Based on our findings, we present a new visualization paradigm for concept hierarchies based on ordinal motifs. These allow for a top-down view on topic spaces. We introduce and demonstrate the applicability of our approach based on a topic model derived from a corpus of scientific papers taken from 32 top machine learning venues.
@preprint{hirth2024geometric,
abstract = {Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an in-depth analysis of topic models is still an open research topic. State-of-the-art methods for interpreting topic models are based on simple visualizations, such as similarity matrices, top-term lists or embeddings, which are limited to a maximum of three dimensions. In this paper, we propose an incidence-geometric method for deriving an ordinal structure from flat topic models, such as non-negative matrix factorization. These enable the analysis of the topic model in a higher (order) dimension and the possibility of extracting conceptual relationships between several topics at once. Due to the use of conceptual scaling, our approach does not introduce any artificial topical relationships, such as artifacts of feature compression. Based on our findings, we present a new visualization paradigm for concept hierarchies based on ordinal motifs. These allow for a top-down view on topic spaces. We introduce and demonstrate the applicability of our approach based on a topic model derived from a corpus of scientific papers taken from 32 top machine learning venues.},
author = {Hirth, Johannes and Hanika, Tom},
keywords = {kde},
title = {The Geometric Structure of Topic Models},
year = 2024
}%0 Generic
%1 hirth2024geometric
%A Hirth, Johannes
%A Hanika, Tom
%D 2024
%T The Geometric Structure of Topic Models
%X Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an in-depth analysis of topic models is still an open research topic. State-of-the-art methods for interpreting topic models are based on simple visualizations, such as similarity matrices, top-term lists or embeddings, which are limited to a maximum of three dimensions. In this paper, we propose an incidence-geometric method for deriving an ordinal structure from flat topic models, such as non-negative matrix factorization. These enable the analysis of the topic model in a higher (order) dimension and the possibility of extracting conceptual relationships between several topics at once. Due to the use of conceptual scaling, our approach does not introduce any artificial topical relationships, such as artifacts of feature compression. Based on our findings, we present a new visualization paradigm for concept hierarchies based on ordinal motifs. These allow for a top-down view on topic spaces. We introduce and demonstrate the applicability of our approach based on a topic model derived from a corpus of scientific papers taken from 32 top machine learning venues. - 1.Priss, U., D{ü}rrschnabel, D.: Rectangular Euler Diagrams and Order Theory. In: Lemanski, J., Johansen, M.W., Manalo, E., Viana, P., Bhattacharjee, R., and Burns, R. (eds.) Diagrammatic Representation and Inference. pp. 165–181. Springer Nature Switzerland, Cham (2024).This paper discusses the relevance of order-theoretical properties, such as order dimension, for determining properties of Euler diagrams, such as whether a given poset can be represented with or without shading. The focus is on linear, tabular and rectangular Euler diagrams with shading and without split attributes and constructions with subdiagrams and embeddings. Euler diagrams are distinguished from geometric containment orders. Basic layout strategies are suggested.
@inproceedings{10.1007/978-3-031-71291-3_14,
abstract = {This paper discusses the relevance of order-theoretical properties, such as order dimension, for determining properties of Euler diagrams, such as whether a given poset can be represented with or without shading. The focus is on linear, tabular and rectangular Euler diagrams with shading and without split attributes and constructions with subdiagrams and embeddings. Euler diagrams are distinguished from geometric containment orders. Basic layout strategies are suggested.},
address = {Cham},
author = {Priss, Uta and D{ü}rrschnabel, Dominik},
booktitle = {Diagrammatic Representation and Inference},
editor = {Lemanski, Jens and Johansen, Mikkel Willum and Manalo, Emmanuel and Viana, Petrucio and Bhattacharjee, Reetu and Burns, Richard},
keywords = {itegpub},
pages = {165--181},
publisher = {Springer Nature Switzerland},
title = {Rectangular Euler Diagrams and Order Theory},
year = 2024
}%0 Conference Paper
%1 10.1007/978-3-031-71291-3_14
%A Priss, Uta
%A D{ü}rrschnabel, Dominik
%B Diagrammatic Representation and Inference
%C Cham
%D 2024
%E Lemanski, Jens
%E Johansen, Mikkel Willum
%E Manalo, Emmanuel
%E Viana, Petrucio
%E Bhattacharjee, Reetu
%E Burns, Richard
%I Springer Nature Switzerland
%P 165--181
%T Rectangular Euler Diagrams and Order Theory
%X This paper discusses the relevance of order-theoretical properties, such as order dimension, for determining properties of Euler diagrams, such as whether a given poset can be represented with or without shading. The focus is on linear, tabular and rectangular Euler diagrams with shading and without split attributes and constructions with subdiagrams and embeddings. Euler diagrams are distinguished from geometric containment orders. Basic layout strategies are suggested.
%@ 978-3-031-71291-3 - 1.Hirth, J.: Conceptual Data Scaling in Machine Learning, (2024). https://doi.org/10.17170/kobra-2024100910940.Information that is intended for human interpretation is frequently represented in a structured manner. This allows for a navigation between individual pieces to find, connect or combine information to gain new insights. Within a structure, we derive knowledge from inference of hierarchical or logical relations between data objects. For unstructured data there are numerous methods to define a data schema based on user interpretations. Afterward, data objects can be aggregated to derive (hierarchical) structures based on common properties. There are four main challenges with respect to the explainability of the derived structures. First, formal procedures are needed to infer knowledge about the data set, or parts of it, from hierarchical structures. Second, what does knowledge inferred from a structure imply for the data set it was derived from? Third, structures may be incomprehensibly large for human interpretation. Methods are needed to reduce structures to smaller representations in a consistent, comprehensible manner that provides control over possibly introduced error. Forth, the original data set does not need to have interpretable features and thus only allow for the inference of structural properties. In order to extract information based on real world properties, we need methods that are able to add such properties. With the presented work, we address these challenges using and extending the rich tool-set of Formal Concept Analysis. Here, data objects are aggregated to closed sets called formal concepts based on (unary) symbolic attributes that they have in common. The process of deriving symbolic attributes is called conceptual scaling and depends on the interpretation of the data by the analyst. The resulting hierarchical structure of concepts is called concept lattice. To infer knowledge from the concept lattice structures we introduce new methods based on sub-structures that are of standardized shape, called ordinal motifs. This novel method allows us to explain the structure of a concept lattice based on geometric aspects. Throughout our work, we focus on data representations from multiple state-of-the-art machine learning algorithms. In all cases, we elaborate extensively on how to interpret these models through derived concept lattices and develop scaling procedures specific to each algorithm. Some of the considered models are black-box models whose internal data representations are numeric with no clear real world semantics. For these, we present a method to link background knowledge to the concept lattice structure. To reduce the complexity of concept lattices we provide a new theoretical framework that allows us to generate (small) views on a concept lattice. These enable more selective and comprehensibly sized explanations for data parts that are of interest. In addition to that, we introduce methods to combine and subtract views from each other, and to identify missing or incorrect parts.
@phdthesis{doi:10.17170/kobra-2024100910940,
abstract = {Information that is intended for human interpretation is frequently represented in a structured manner. This allows for a navigation between individual pieces to find, connect or combine information to gain new insights. Within a structure, we derive knowledge from inference of hierarchical or logical relations between data objects. For unstructured data there are numerous methods to define a data schema based on user interpretations. Afterward, data objects can be aggregated to derive (hierarchical) structures based on common properties. There are four main challenges with respect to the explainability of the derived structures. First, formal procedures are needed to infer knowledge about the data set, or parts of it, from hierarchical structures. Second, what does knowledge inferred from a structure imply for the data set it was derived from? Third, structures may be incomprehensibly large for human interpretation. Methods are needed to reduce structures to smaller representations in a consistent, comprehensible manner that provides control over possibly introduced error. Forth, the original data set does not need to have interpretable features and thus only allow for the inference of structural properties. In order to extract information based on real world properties, we need methods that are able to add such properties. With the presented work, we address these challenges using and extending the rich tool-set of Formal Concept Analysis. Here, data objects are aggregated to closed sets called formal concepts based on (unary) symbolic attributes that they have in common. The process of deriving symbolic attributes is called conceptual scaling and depends on the interpretation of the data by the analyst. The resulting hierarchical structure of concepts is called concept lattice. To infer knowledge from the concept lattice structures we introduce new methods based on sub-structures that are of standardized shape, called ordinal motifs. This novel method allows us to explain the structure of a concept lattice based on geometric aspects. Throughout our work, we focus on data representations from multiple state-of-the-art machine learning algorithms. In all cases, we elaborate extensively on how to interpret these models through derived concept lattices and develop scaling procedures specific to each algorithm. Some of the considered models are black-box models whose internal data representations are numeric with no clear real world semantics. For these, we present a method to link background knowledge to the concept lattice structure. To reduce the complexity of concept lattices we provide a new theoretical framework that allows us to generate (small) views on a concept lattice. These enable more selective and comprehensibly sized explanations for data parts that are of interest. In addition to that, we introduce methods to combine and subtract views from each other, and to identify missing or incorrect parts.},
author = {Hirth, Johannes},
keywords = {Knowldege~Representation},
school = {Kassel, Universität Kassel, Fachbereich Elektrotechnik/Informatik},
title = {Conceptual Data Scaling in Machine Learning},
year = 2024
}%0 Thesis
%1 doi:10.17170/kobra-2024100910940
%A Hirth, Johannes
%D 2024
%R 10.17170/kobra-2024100910940
%T Conceptual Data Scaling in Machine Learning
%X Information that is intended for human interpretation is frequently represented in a structured manner. This allows for a navigation between individual pieces to find, connect or combine information to gain new insights. Within a structure, we derive knowledge from inference of hierarchical or logical relations between data objects. For unstructured data there are numerous methods to define a data schema based on user interpretations. Afterward, data objects can be aggregated to derive (hierarchical) structures based on common properties. There are four main challenges with respect to the explainability of the derived structures. First, formal procedures are needed to infer knowledge about the data set, or parts of it, from hierarchical structures. Second, what does knowledge inferred from a structure imply for the data set it was derived from? Third, structures may be incomprehensibly large for human interpretation. Methods are needed to reduce structures to smaller representations in a consistent, comprehensible manner that provides control over possibly introduced error. Forth, the original data set does not need to have interpretable features and thus only allow for the inference of structural properties. In order to extract information based on real world properties, we need methods that are able to add such properties. With the presented work, we address these challenges using and extending the rich tool-set of Formal Concept Analysis. Here, data objects are aggregated to closed sets called formal concepts based on (unary) symbolic attributes that they have in common. The process of deriving symbolic attributes is called conceptual scaling and depends on the interpretation of the data by the analyst. The resulting hierarchical structure of concepts is called concept lattice. To infer knowledge from the concept lattice structures we introduce new methods based on sub-structures that are of standardized shape, called ordinal motifs. This novel method allows us to explain the structure of a concept lattice based on geometric aspects. Throughout our work, we focus on data representations from multiple state-of-the-art machine learning algorithms. In all cases, we elaborate extensively on how to interpret these models through derived concept lattices and develop scaling procedures specific to each algorithm. Some of the considered models are black-box models whose internal data representations are numeric with no clear real world semantics. For these, we present a method to link background knowledge to the concept lattice structure. To reduce the complexity of concept lattices we provide a new theoretical framework that allows us to generate (small) views on a concept lattice. These enable more selective and comprehensibly sized explanations for data parts that are of interest. In addition to that, we introduce methods to combine and subtract views from each other, and to identify missing or incorrect parts. - 1.Draude, C., Dürrschnabel, D., Hirth, J., Horn, V., Kropf, J., Lamla, J., Stumme, G., Uhlmann, M.: Conceptual Mapping of Controversies. In: Cabrera, I.P., Ferré, S., and Obiedkov, S. (eds.) Conceptual Knowledge Structures. pp. 201–216. Springer Nature Switzerland, Cham (2024).With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these methods can be used to assess the diversity, complexity and potential bias of controversies. In addition to that, we discuss how the diagrams of concept lattices can be used to navigate between news articles.
@inproceedings{10.1007/978-3-031-67868-4_14,
abstract = {With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these methods can be used to assess the diversity, complexity and potential bias of controversies. In addition to that, we discuss how the diagrams of concept lattices can be used to navigate between news articles.},
address = {Cham},
author = {Draude, Claude and Dürrschnabel, Dominik and Hirth, Johannes and Horn, Viktoria and Kropf, Jonathan and Lamla, J{ö}rn and Stumme, Gerd and Uhlmann, Markus},
booktitle = {Conceptual Knowledge Structures},
editor = {Cabrera, Inma P. and Ferré, Sébastien and Obiedkov, Sergei},
keywords = {itegpub},
pages = {201--216},
publisher = {Springer Nature Switzerland},
title = {Conceptual Mapping of Controversies},
year = 2024
}%0 Conference Paper
%1 10.1007/978-3-031-67868-4_14
%A Draude, Claude
%A Dürrschnabel, Dominik
%A Hirth, Johannes
%A Horn, Viktoria
%A Kropf, Jonathan
%A Lamla, J{ö}rn
%A Stumme, Gerd
%A Uhlmann, Markus
%B Conceptual Knowledge Structures
%C Cham
%D 2024
%E Cabrera, Inma P.
%E Ferré, Sébastien
%E Obiedkov, Sergei
%I Springer Nature Switzerland
%P 201--216
%T Conceptual Mapping of Controversies
%X With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these methods can be used to assess the diversity, complexity and potential bias of controversies. In addition to that, we discuss how the diagrams of concept lattices can be used to navigate between news articles.
%@ 978-3-031-67868-4 - 1.Hanika, T., Hille, T.: What is the Intrinsic Dimension of Your Binary Data? - and How to Compute it Quickly. In: Cabrera, I.P., Ferr{{é}}, S., and Obiedkov, S.A. (eds.) Conceptual Knowledge Structures - First International Joint Conference, {CONCEPTS} 2024, C{{á}}diz, Spain, September 9-13, 2024, Proceedings. pp. 97–112. Springer (2024). https://doi.org/10.1007/978-3-031-67868-4\_7.
@inproceedings{DBLP:conf/concepts/HanikaH24,
author = {Hanika, Tom and Hille, Tobias},
booktitle = {Conceptual Knowledge Structures - First International Joint Conference, {CONCEPTS} 2024, C{{á}}diz, Spain, September 9-13, 2024, Proceedings},
editor = {Cabrera, Inma P. and Ferr{{é}}, S{{é}}bastien and Obiedkov, Sergei A.},
keywords = {itegpub},
pages = {97--112},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {What is the Intrinsic Dimension of Your Binary Data? - and How to Compute it Quickly},
volume = 14914,
year = 2024
}%0 Conference Paper
%1 DBLP:conf/concepts/HanikaH24
%A Hanika, Tom
%A Hille, Tobias
%B Conceptual Knowledge Structures - First International Joint Conference, {CONCEPTS} 2024, C{{á}}diz, Spain, September 9-13, 2024, Proceedings
%D 2024
%E Cabrera, Inma P.
%E Ferr{{é}}, S{{é}}bastien
%E Obiedkov, Sergei A.
%I Springer
%P 97--112
%R 10.1007/978-3-031-67868-4\_7
%T What is the Intrinsic Dimension of Your Binary Data? - and How to Compute it Quickly
%U https://doi.org/10.1007/978-3-031-67868-4\_7
%V 14914 - 1.Hanika, T., Jäschke, R.: A Repository for Formal Contexts. In: Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures (2024).Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this.
@inproceedings{hanika2024repository,
abstract = {Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this.},
author = {Hanika, Tom and Jäschke, Robert},
booktitle = {Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures},
keywords = {repository},
title = {A Repository for Formal Contexts},
year = 2024
}%0 Conference Paper
%1 hanika2024repository
%A Hanika, Tom
%A Jäschke, Robert
%B Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures
%D 2024
%T A Repository for Formal Contexts
%U https://arxiv.org/abs/2404.04344
%X Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this. - 1.Hirth, J., Horn, V., Stumme, G., Hanika, T.: Ordinal motifs in lattices. Information Sciences. 659, 120009 (2024). https://doi.org/https://doi.org/10.1016/j.ins.2023.120009.
@article{HIRTH2024120009,
author = {Hirth, Johannes and Horn, Viktoria and Stumme, Gerd and Hanika, Tom},
journal = {Information Sciences},
keywords = {itegpub},
pages = 120009,
title = {Ordinal motifs in lattices},
volume = 659,
year = 2024
}%0 Journal Article
%1 HIRTH2024120009
%A Hirth, Johannes
%A Horn, Viktoria
%A Stumme, Gerd
%A Hanika, Tom
%D 2024
%J Information Sciences
%P 120009
%R https://doi.org/10.1016/j.ins.2023.120009
%T Ordinal motifs in lattices
%U https://www.sciencedirect.com/science/article/pii/S0020025523015943
%V 659 - 1.D{ü}rrschnabel, D., Priss, U.: Realizability of Rectangular Euler Diagrams. In: Cabrera, I.P., Ferr{é}, S., and Obiedkov, S. (eds.) Conceptual Knowledge Structures. pp. 149–165. Springer Nature Switzerland, Cham (2024).Euler diagrams are a tool for the graphical representation of set relations. Due to their simple way of visualizing elements in the sets by geometric containment, they are easily readable by an inexperienced reader. Euler diagrams where the sets are visualized as aligned rectangles are of special interest. In this work, we link the existence of such rectangular Euler diagrams to the order dimension of an associated order relation. For this, we consider Euler diagrams in one and two dimensions. In the one-dimensional case, this correspondence provides us with a polynomial-time algorithm to compute the Euler diagrams, while the two-dimensional case is linked to an NP-complete problem which we approach with an exponential-time algorithm.
@inproceedings{10.1007/978-3-031-67868-4_11,
abstract = {Euler diagrams are a tool for the graphical representation of set relations. Due to their simple way of visualizing elements in the sets by geometric containment, they are easily readable by an inexperienced reader. Euler diagrams where the sets are visualized as aligned rectangles are of special interest. In this work, we link the existence of such rectangular Euler diagrams to the order dimension of an associated order relation. For this, we consider Euler diagrams in one and two dimensions. In the one-dimensional case, this correspondence provides us with a polynomial-time algorithm to compute the Euler diagrams, while the two-dimensional case is linked to an NP-complete problem which we approach with an exponential-time algorithm.},
address = {Cham},
author = {D{ü}rrschnabel, Dominik and Priss, Uta},
booktitle = {Conceptual Knowledge Structures},
editor = {Cabrera, Inma P. and Ferr{é}, S{é}bastien and Obiedkov, Sergei},
keywords = {itegpub},
pages = {149--165},
publisher = {Springer Nature Switzerland},
title = {Realizability of Rectangular Euler Diagrams},
year = 2024
}%0 Conference Paper
%1 10.1007/978-3-031-67868-4_11
%A D{ü}rrschnabel, Dominik
%A Priss, Uta
%B Conceptual Knowledge Structures
%C Cham
%D 2024
%E Cabrera, Inma P.
%E Ferr{é}, S{é}bastien
%E Obiedkov, Sergei
%I Springer Nature Switzerland
%P 149--165
%T Realizability of Rectangular Euler Diagrams
%X Euler diagrams are a tool for the graphical representation of set relations. Due to their simple way of visualizing elements in the sets by geometric containment, they are easily readable by an inexperienced reader. Euler diagrams where the sets are visualized as aligned rectangles are of special interest. In this work, we link the existence of such rectangular Euler diagrams to the order dimension of an associated order relation. For this, we consider Euler diagrams in one and two dimensions. In the one-dimensional case, this correspondence provides us with a polynomial-time algorithm to compute the Euler diagrams, while the two-dimensional case is linked to an NP-complete problem which we approach with an exponential-time algorithm.
%@ 978-3-031-67868-4 - 1.Draude, C., D{ü}rrschnabel, D., Hirth, J., Horn, V., Kropf, J., Lamla, J., Stumme, G., Uhlmann, M.: Conceptual Mapping of Controversies. In: Cabrera, I.P., Ferr{é}, S., and Obiedkov, S. (eds.) Conceptual Knowledge Structures. pp. 201–216. Springer Nature Switzerland, Cham (2024).With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these methods can be used to assess the diversity, complexity and potential bias of controversies. In addition to that, we discuss how the diagrams of concept lattices can be used to navigate between news articles.
@inproceedings{10.1007/978-3-031-67868-4_14,
abstract = {With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these methods can be used to assess the diversity, complexity and potential bias of controversies. In addition to that, we discuss how the diagrams of concept lattices can be used to navigate between news articles.},
address = {Cham},
author = {Draude, Claude and D{ü}rrschnabel, Dominik and Hirth, Johannes and Horn, Viktoria and Kropf, Jonathan and Lamla, J{ö}rn and Stumme, Gerd and Uhlmann, Markus},
booktitle = {Conceptual Knowledge Structures},
editor = {Cabrera, Inma P. and Ferr{é}, S{é}bastien and Obiedkov, Sergei},
keywords = {formal_concept_analysis},
pages = {201--216},
publisher = {Springer Nature Switzerland},
title = {Conceptual Mapping of Controversies},
year = 2024
}%0 Conference Paper
%1 10.1007/978-3-031-67868-4_14
%A Draude, Claude
%A D{ü}rrschnabel, Dominik
%A Hirth, Johannes
%A Horn, Viktoria
%A Kropf, Jonathan
%A Lamla, J{ö}rn
%A Stumme, Gerd
%A Uhlmann, Markus
%B Conceptual Knowledge Structures
%C Cham
%D 2024
%E Cabrera, Inma P.
%E Ferr{é}, S{é}bastien
%E Obiedkov, Sergei
%I Springer Nature Switzerland
%P 201--216
%T Conceptual Mapping of Controversies
%X With our work, we contribute towards a qualitative analysis of the discourse on controversies in online news media. For this, we employ Formal Concept Analysis and the economics of conventions to derive conceptual controversy maps. In our experiments, we analyze two maps from different news journals with methods from ordinal data science. We show how these methods can be used to assess the diversity, complexity and potential bias of controversies. In addition to that, we discuss how the diagrams of concept lattices can be used to navigate between news articles.
%@ 978-3-031-67868-4
2023
- 1.Hirth, J., Horn, V., Stumme, G., Hanika, T.: Automatic Textual Explanations of Concept Lattices. In: Ojeda{-}Aciego, M., Sauerwald, K., and Jäschke, R. (eds.) Graph-Based Representation and Reasoning - 28th International Conference on Conceptual Structures, {ICCS} 2023, Berlin, Germany, September 11-13, 2023, Proceedings. pp. 138–152 (2023). https://doi.org/doi.org/10.1007/978-3-031-40960-8_12.Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textual explanations for lattices using standard scales. Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales. We show the computational complexity of identifying a small number of standard scales that cover most of the lattice structure. For these, we provide textual explanation templates, which can be applied to any occurrence of a scale in any data domain. These templates are derived using principles from human-computer interaction and allow for a comprehensive textual explanation of lattices. We demonstrate our approach on the spices planner data set, which is a medium sized formal context comprised of fifty-six meals (objects) and thirty-seven spices (attributes). The resulting 531 formal concepts can be covered by means of about 100 standard scales.
@inproceedings{hirth2023automatic,
abstract = {Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textual explanations for lattices using standard scales. Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales. We show the computational complexity of identifying a small number of standard scales that cover most of the lattice structure. For these, we provide textual explanation templates, which can be applied to any occurrence of a scale in any data domain. These templates are derived using principles from human-computer interaction and allow for a comprehensive textual explanation of lattices. We demonstrate our approach on the spices planner data set, which is a medium sized formal context comprised of fifty-six meals (objects) and thirty-seven spices (attributes). The resulting 531 formal concepts can be covered by means of about 100 standard scales.},
author = {Hirth, Johannes and Horn, Viktoria and Stumme, Gerd and Hanika, Tom},
booktitle = {Graph-Based Representation and Reasoning - 28th International Conference on Conceptual Structures, {ICCS} 2023, Berlin, Germany, September 11-13, 2023, Proceedings},
editor = {Ojeda{-}Aciego, Manuel and Sauerwald, Kai and Jäschke, Robert},
keywords = {itegpub},
pages = {138--152},
title = {Automatic Textual Explanations of Concept Lattices},
volume = 14133,
year = 2023
}%0 Conference Paper
%1 hirth2023automatic
%A Hirth, Johannes
%A Horn, Viktoria
%A Stumme, Gerd
%A Hanika, Tom
%B Graph-Based Representation and Reasoning - 28th International Conference on Conceptual Structures, {ICCS} 2023, Berlin, Germany, September 11-13, 2023, Proceedings
%D 2023
%E Ojeda{-}Aciego, Manuel
%E Sauerwald, Kai
%E Jäschke, Robert
%P 138--152
%R doi.org/10.1007/978-3-031-40960-8_12
%T Automatic Textual Explanations of Concept Lattices
%U http://arxiv.org/abs/2304.08093
%V 14133
%X Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textual explanations for lattices using standard scales. Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales. We show the computational complexity of identifying a small number of standard scales that cover most of the lattice structure. For these, we provide textual explanation templates, which can be applied to any occurrence of a scale in any data domain. These templates are derived using principles from human-computer interaction and allow for a comprehensive textual explanation of lattices. We demonstrate our approach on the spices planner data set, which is a medium sized formal context comprised of fifty-six meals (objects) and thirty-seven spices (attributes). The resulting 531 formal concepts can be covered by means of about 100 standard scales. - 1.Budde, K.B., Rellstab, C., Heuertz, M., Gugerli, F., Hanika, T., Verdú, M., Pausas, J.G., González-Martínez, S.C.: Divergent selection in a Mediterranean pine on local spatial scales. Journal of Ecology. n/a, (2023). https://doi.org/https://doi.org/10.1111/1365-2745.14231.Abstract The effects of selection on an organism's genome are hard to detect on small spatial scales, as gene flow can swamp signatures of local adaptation. Therefore, most genome scans to detect signatures of environmental selection are performed on large spatial scales; however, divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants. Here, we hypothesised that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in the genomes of long-lived organisms. To test this, we investigated paired south- versus north-facing Pinus pinaster stands on the local scale, with trees growing in close vicinity (≤820 m distance between paired south- and north-facing stands), in a Mediterranean mountain area. While trees on north-facing slopes experience less radiation, trees on south-facing slopes suffer from especially harsh conditions, particularly during the dry summer season. Two outlier analyses consistently revealed five putatively adaptive loci (out of 4034), in candidate genes two of which encoded non-synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Permutation tests demonstrated that our findings were robust. Functional annotation of these candidate genes revealed biological functions related to abiotic stress response, such as water availability, in other plant species. Synthesis. Our study highlights how divergent selection in heterogeneous microenvironments shapes and maintains the functional genetic variation within populations of long-lived forest tree species, being the first to focus on adaptive genetic divergence between south- and north-facing slopes within continuous forest stands. This is especially relevant in the current context of climate change, as this variation is at the base of plant population responses to future climate.
@article{https://doi.org/10.1111/1365-2745.14231,
abstract = {Abstract The effects of selection on an organism's genome are hard to detect on small spatial scales, as gene flow can swamp signatures of local adaptation. Therefore, most genome scans to detect signatures of environmental selection are performed on large spatial scales; however, divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants. Here, we hypothesised that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in the genomes of long-lived organisms. To test this, we investigated paired south- versus north-facing Pinus pinaster stands on the local scale, with trees growing in close vicinity (≤820 m distance between paired south- and north-facing stands), in a Mediterranean mountain area. While trees on north-facing slopes experience less radiation, trees on south-facing slopes suffer from especially harsh conditions, particularly during the dry summer season. Two outlier analyses consistently revealed five putatively adaptive loci (out of 4034), in candidate genes two of which encoded non-synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Permutation tests demonstrated that our findings were robust. Functional annotation of these candidate genes revealed biological functions related to abiotic stress response, such as water availability, in other plant species. Synthesis. Our study highlights how divergent selection in heterogeneous microenvironments shapes and maintains the functional genetic variation within populations of long-lived forest tree species, being the first to focus on adaptive genetic divergence between south- and north-facing slopes within continuous forest stands. This is especially relevant in the current context of climate change, as this variation is at the base of plant population responses to future climate.},
author = {Budde, Katharina B. and Rellstab, Christian and Heuertz, Myriam and Gugerli, Felix and Hanika, Tom and Verdú, Miguel and Pausas, Juli G. and González-Martínez, Santiago C.},
journal = {Journal of Ecology},
keywords = {itegpub},
number = {n/a},
title = {Divergent selection in a Mediterranean pine on local spatial scales},
volume = {n/a},
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}%0 Journal Article
%1 https://doi.org/10.1111/1365-2745.14231
%A Budde, Katharina B.
%A Rellstab, Christian
%A Heuertz, Myriam
%A Gugerli, Felix
%A Hanika, Tom
%A Verdú, Miguel
%A Pausas, Juli G.
%A González-Martínez, Santiago C.
%D 2023
%J Journal of Ecology
%N n/a
%R https://doi.org/10.1111/1365-2745.14231
%T Divergent selection in a Mediterranean pine on local spatial scales
%U https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/1365-2745.14231
%V n/a
%X Abstract The effects of selection on an organism's genome are hard to detect on small spatial scales, as gene flow can swamp signatures of local adaptation. Therefore, most genome scans to detect signatures of environmental selection are performed on large spatial scales; however, divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants. Here, we hypothesised that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in the genomes of long-lived organisms. To test this, we investigated paired south- versus north-facing Pinus pinaster stands on the local scale, with trees growing in close vicinity (≤820 m distance between paired south- and north-facing stands), in a Mediterranean mountain area. While trees on north-facing slopes experience less radiation, trees on south-facing slopes suffer from especially harsh conditions, particularly during the dry summer season. Two outlier analyses consistently revealed five putatively adaptive loci (out of 4034), in candidate genes two of which encoded non-synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Permutation tests demonstrated that our findings were robust. Functional annotation of these candidate genes revealed biological functions related to abiotic stress response, such as water availability, in other plant species. Synthesis. Our study highlights how divergent selection in heterogeneous microenvironments shapes and maintains the functional genetic variation within populations of long-lived forest tree species, being the first to focus on adaptive genetic divergence between south- and north-facing slopes within continuous forest stands. This is especially relevant in the current context of climate change, as this variation is at the base of plant population responses to future climate. - 1.Felde, M., Stumme, G.: Interactive collaborative exploration using incomplete contexts. Data & Knowledge Engineering. 143, 102104 (2023). https://doi.org/10.1016/j.datak.2022.102104.
@article{Felde_2023,
author = {Felde, Maximilian and Stumme, Gerd},
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month = {01},
pages = 102104,
publisher = {Elsevier {BV}},
title = {Interactive collaborative exploration using incomplete contexts},
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%V 143 - 1.Felde, M., Koyda, M.: Interval-dismantling for lattices. International Journal of Approximate Reasoning. 159, 108931 (2023). https://doi.org/10.1016/j.ijar.2023.108931.Dismantling allows for the removal of elements from a poset, or in our case lattice, without disturbing the remaining structure. In this paper we have extended the notion of dismantling by single elements to the dismantling by intervals in a lattice. We utilize theory from Formal Concept Analysis (FCA) to show that lattices dismantled by intervals correspond to closed subrelations in the respective formal context, and that there exists a unique core with respect to dismantling by intervals. Furthermore, we show that dismantling intervals can be identified directly in the formal context utilizing a characterization via arrow relations and provide an algorithm to compute all dismantling intervals.
@article{FELDE2023108931,
abstract = {Dismantling allows for the removal of elements from a poset, or in our case lattice, without disturbing the remaining structure. In this paper we have extended the notion of dismantling by single elements to the dismantling by intervals in a lattice. We utilize theory from Formal Concept Analysis (FCA) to show that lattices dismantled by intervals correspond to closed subrelations in the respective formal context, and that there exists a unique core with respect to dismantling by intervals. Furthermore, we show that dismantling intervals can be identified directly in the formal context utilizing a characterization via arrow relations and provide an algorithm to compute all dismantling intervals.},
author = {Felde, Maximilian and Koyda, Maren},
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%V 159
%X Dismantling allows for the removal of elements from a poset, or in our case lattice, without disturbing the remaining structure. In this paper we have extended the notion of dismantling by single elements to the dismantling by intervals in a lattice. We utilize theory from Formal Concept Analysis (FCA) to show that lattices dismantled by intervals correspond to closed subrelations in the respective formal context, and that there exists a unique core with respect to dismantling by intervals. Furthermore, we show that dismantling intervals can be identified directly in the formal context utilizing a characterization via arrow relations and provide an algorithm to compute all dismantling intervals. - 1.Stubbemann, M., Hanika, T., Schneider, F.M.: Intrinsic Dimension for Large-Scale Geometric Learning. Transactions on Machine Learning Research. (2023).
@article{stubbemann2022intrinsic,
author = {Stubbemann, Maximilian and Hanika, Tom and Schneider, Friedrich Martin},
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%U https://openreview.net/forum?id=85BfDdYMBY - 1.Stubbemann, M., Stumme, G.: The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks. In: Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, {ECML} {PKDD} 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part {III}. pp. 177–192. Springer (2023). https://doi.org/10.1007/978-3-031-43418-1\_11.
@inproceedings{DBLP:conf/pkdd/StubbemannS23,
author = {Stubbemann, Maximilian and Stumme, Gerd},
booktitle = {Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, {ECML} {PKDD} 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part {III}},
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pages = {177--192},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks},
volume = 14171,
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}%0 Conference Paper
%1 DBLP:conf/pkdd/StubbemannS23
%A Stubbemann, Maximilian
%A Stumme, Gerd
%B Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, {ECML} {PKDD} 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part {III}
%D 2023
%I Springer
%P 177--192
%R 10.1007/978-3-031-43418-1\_11
%T The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks
%U https://doi.org/10.1007/978-3-031-43418-1_11
%V 14171 - 1.Dürrschnabel, D., Hanika, T., Stumme, G.: Drawing Order Diagrams Through Two-Dimension Extension. Journal of Graph Algorithms and Applications. 27, 783–802 (2023). https://doi.org/10.7155/jgaa.00645.
@article{drrschnabel2023drawing,
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%V 27 - 1.Koyda, M., Stumme, G.: Factorizing Lattices by Interval Relations. Int. J. Approx. Reason. 157, 70–87 (2023).
@article{koyda2023factorizing,
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%J Int. J. Approx. Reason.
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%U http://dblp.uni-trier.de/db/journals/ijar/ijar157.html#KoydaS23
%V 157 - 1.Hirth, J., Horn, V., Stumme, G., Hanika, T.: Ordinal Motifs in Lattices, https://arxiv.org/abs/2304.04827, (2023).Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of a large and high-dimensional lattice into a set of understandably large parts. With the present work we propose /ordinal motifs/ as analytical units of meaning. We study these ordinal substructures (or standard scales) through (full) scale-measures of formal contexts from the field of formal concept analysis. We show that the underlying decision problems are NP-complete and provide results on how one can incrementally identify ordinal motifs to save computational effort. Accompanying our theoretical results, we demonstrate how ordinal motifs can be leveraged to retrieve basic meaning from a medium sized ordinal data set.
@misc{hirth2023ordinal,
abstract = {Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of a large and high-dimensional lattice into a set of understandably large parts. With the present work we propose /ordinal motifs/ as analytical units of meaning. We study these ordinal substructures (or standard scales) through (full) scale-measures of formal contexts from the field of formal concept analysis. We show that the underlying decision problems are NP-complete and provide results on how one can incrementally identify ordinal motifs to save computational effort. Accompanying our theoretical results, we demonstrate how ordinal motifs can be leveraged to retrieve basic meaning from a medium sized ordinal data set.},
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%1 hirth2023ordinal
%A Hirth, Johannes
%A Horn, Viktoria
%A Stumme, Gerd
%A Hanika, Tom
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%U https://arxiv.org/abs/2304.04827
%X Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of a large and high-dimensional lattice into a set of understandably large parts. With the present work we propose /ordinal motifs/ as analytical units of meaning. We study these ordinal substructures (or standard scales) through (full) scale-measures of formal contexts from the field of formal concept analysis. We show that the underlying decision problems are NP-complete and provide results on how one can incrementally identify ordinal motifs to save computational effort. Accompanying our theoretical results, we demonstrate how ordinal motifs can be leveraged to retrieve basic meaning from a medium sized ordinal data set. - 1.Dürrschnabel, D.: Explaining and Visualizing Structural Knowledge in Bipartite Graphs, https://kobra.uni-kassel.de/handle/123456789/14847, (2023). https://doi.org/10.17170/KOBRA-202306048157.
@phdthesis{https://doi.org/10.17170/kobra-202306048157,
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}%0 Thesis
%1 https://doi.org/10.17170/kobra-202306048157
%A Dürrschnabel, Dominik
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%T Explaining and Visualizing Structural Knowledge in Bipartite Graphs
%U https://kobra.uni-kassel.de/handle/123456789/14847 - 1.Stumme, G., Dürrschnabel, D., Hanika, T.: Towards Ordinal Data Science. Transactions on Graph Data and Knowledge. 1, 6:1–6:39 (2023). https://doi.org/10.4230/TGDK.1.1.6.
@article{DBLP:journals/tgdk/StummeDH23,
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%V 1 - 1.Stubbemann, M., Hille, T., Hanika, T.: Selecting Features by their Resilience to the Curse of Dimensionality. (2023).
@article{stubbemann2023selecting,
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title = {Selecting Features by their Resilience to the Curse of Dimensionality},
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%1 stubbemann2023selecting
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%A Hanika, Tom
%D 2023
%T Selecting Features by their Resilience to the Curse of Dimensionality - 1.Ganter, B., Hanika, T., Hirth, J.: Scaling Dimension. In: Dürrschnabel, D. and López-Rodríguez, D. (eds.) Formal Concept Analysis - 17th International Conference, ICFCA 2023, Kassel, Germany, July 17-21, 2023, Proceedings. pp. 64–77. Springer (2023). https://doi.org/10.1007/978-3-031-35949-1_5.
@inproceedings{DBLP:conf/icfca/GanterHH23,
author = {Ganter, Bernhard and Hanika, Tom and Hirth, Johannes},
booktitle = {Formal Concept Analysis - 17th International Conference, ICFCA 2023, Kassel, Germany, July 17-21, 2023, Proceedings},
editor = {Dürrschnabel, Dominik and López-Rodríguez, Domingo},
keywords = {itegpub},
pages = {64--77},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Scaling Dimension},
volume = 13934,
year = 2023
}%0 Conference Paper
%1 DBLP:conf/icfca/GanterHH23
%A Ganter, Bernhard
%A Hanika, Tom
%A Hirth, Johannes
%B Formal Concept Analysis - 17th International Conference, ICFCA 2023, Kassel, Germany, July 17-21, 2023, Proceedings
%D 2023
%E Dürrschnabel, Dominik
%E López-Rodríguez, Domingo
%I Springer
%P 64--77
%R 10.1007/978-3-031-35949-1_5
%T Scaling Dimension
%U https://doi.org/10.1007/978-3-031-35949-1_5
%V 13934 - 1.Hanika, T., Hirth, J.: Conceptual Views on Tree Ensemble Classifiers. International Journal of Approximate Reasoning. 108930 (2023). https://doi.org/https://doi.org/10.1016/j.ijar.2023.108930.Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are often used to compensate for this disadvantage. Yet, their ability for local explanations, and in particular for global explanations, is limited. In the present work we propose an algebraic method, rooted in lattice theory, for the (global) explanation of tree ensembles. In detail, we introduce two novel conceptual views on tree ensemble classifiers and demonstrate their explanatory capabilities on Random Forests that were trained with standard parameters.
@article{https://doi.org/10.48550/arxiv.2302.05270,
abstract = {Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are often used to compensate for this disadvantage. Yet, their ability for local explanations, and in particular for global explanations, is limited. In the present work we propose an algebraic method, rooted in lattice theory, for the (global) explanation of tree ensembles. In detail, we introduce two novel conceptual views on tree ensemble classifiers and demonstrate their explanatory capabilities on Random Forests that were trained with standard parameters.},
author = {Hanika, Tom and Hirth, Johannes},
journal = {International Journal of Approximate Reasoning},
keywords = {itegpub},
pages = 108930,
title = {Conceptual Views on Tree Ensemble Classifiers},
year = 2023
}%0 Journal Article
%1 https://doi.org/10.48550/arxiv.2302.05270
%A Hanika, Tom
%A Hirth, Johannes
%D 2023
%J International Journal of Approximate Reasoning
%P 108930
%R https://doi.org/10.1016/j.ijar.2023.108930
%T Conceptual Views on Tree Ensemble Classifiers
%U https://www.sciencedirect.com/science/article/pii/S0888613X23000610
%X Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are often used to compensate for this disadvantage. Yet, their ability for local explanations, and in particular for global explanations, is limited. In the present work we propose an algebraic method, rooted in lattice theory, for the (global) explanation of tree ensembles. In detail, we introduce two novel conceptual views on tree ensemble classifiers and demonstrate their explanatory capabilities on Random Forests that were trained with standard parameters. - 1.Dürrschnabel, D., Stumme, G.: Greedy Discovery of Ordinal Factors, http://arxiv.org/abs/2302.11554, (2023).In large datasets, it is hard to discover and analyze structure. It is thus common to introduce tags or keywords for the items. In applications, such datasets are then filtered based on these tags. Still, even medium-sized datasets with a few tags result in complex and for humans hard-to-navigate systems. In this work, we adopt the method of ordinal factor analysis to address this problem. An ordinal factor arranges a subset of the tags in a linear order based on their underlying structure. A complete ordinal factorization, which consists of such ordinal factors, precisely represents the original dataset. Based on such an ordinal factorization, we provide a way to discover and explain relationships between different items and attributes in the dataset. However, computing even just one ordinal factor of high cardinality is computationally complex. We thus propose the greedy algorithm in this work. This algorithm extracts ordinal factors using already existing fast algorithms developed in formal concept analysis. Then, we leverage to propose a comprehensive way to discover relationships in the dataset. We furthermore introduce a distance measure based on the representation emerging from the ordinal factorization to discover similar items. To evaluate the method, we conduct a case study on different datasets.
@misc{durrschnabel2023greedy,
abstract = {In large datasets, it is hard to discover and analyze structure. It is thus common to introduce tags or keywords for the items. In applications, such datasets are then filtered based on these tags. Still, even medium-sized datasets with a few tags result in complex and for humans hard-to-navigate systems. In this work, we adopt the method of ordinal factor analysis to address this problem. An ordinal factor arranges a subset of the tags in a linear order based on their underlying structure. A complete ordinal factorization, which consists of such ordinal factors, precisely represents the original dataset. Based on such an ordinal factorization, we provide a way to discover and explain relationships between different items and attributes in the dataset. However, computing even just one ordinal factor of high cardinality is computationally complex. We thus propose the greedy algorithm in this work. This algorithm extracts ordinal factors using already existing fast algorithms developed in formal concept analysis. Then, we leverage to propose a comprehensive way to discover relationships in the dataset. We furthermore introduce a distance measure based on the representation emerging from the ordinal factorization to discover similar items. To evaluate the method, we conduct a case study on different datasets.},
author = {Dürrschnabel, Dominik and Stumme, Gerd},
keywords = {itegpub},
note = {cite arxiv:2302.11554Comment: 11 pages, 6 figures, 2 tables, 3 algorithms},
title = {Greedy Discovery of Ordinal Factors},
year = 2023
}%0 Generic
%1 durrschnabel2023greedy
%A Dürrschnabel, Dominik
%A Stumme, Gerd
%D 2023
%T Greedy Discovery of Ordinal Factors
%U http://arxiv.org/abs/2302.11554
%X In large datasets, it is hard to discover and analyze structure. It is thus common to introduce tags or keywords for the items. In applications, such datasets are then filtered based on these tags. Still, even medium-sized datasets with a few tags result in complex and for humans hard-to-navigate systems. In this work, we adopt the method of ordinal factor analysis to address this problem. An ordinal factor arranges a subset of the tags in a linear order based on their underlying structure. A complete ordinal factorization, which consists of such ordinal factors, precisely represents the original dataset. Based on such an ordinal factorization, we provide a way to discover and explain relationships between different items and attributes in the dataset. However, computing even just one ordinal factor of high cardinality is computationally complex. We thus propose the greedy algorithm in this work. This algorithm extracts ordinal factors using already existing fast algorithms developed in formal concept analysis. Then, we leverage to propose a comprehensive way to discover relationships in the dataset. We furthermore introduce a distance measure based on the representation emerging from the ordinal factorization to discover similar items. To evaluate the method, we conduct a case study on different datasets. - 1.Dürrschnabel, D., Stumme, G.: Maximal Ordinal Two-Factorizations, http://arxiv.org/abs/2304.03338, (2023).Given a formal context, an ordinal factor is a subset of its incidence relation that forms a chain in the concept lattice, i.e., a part of the dataset that corresponds to a linear order. To visualize the data in a formal context, Ganter and Glodeanu proposed a biplot based on two ordinal factors. For the biplot to be useful, it is important that these factors comprise as much data points as possible, i.e., that they cover a large part of the incidence relation. In this work, we investigate such ordinal two-factorizations. First, we investigate for formal contexts that omit ordinal two-factorizations the disjointness of the two factors. Then, we show that deciding on the existence of two-factorizations of a given size is an NP-complete problem which makes computing maximal factorizations computationally expensive. Finally, we provide the algorithm Ord2Factor that allows us to compute large ordinal two-factorizations.
@misc{durrschnabel2023maximal,
abstract = {Given a formal context, an ordinal factor is a subset of its incidence relation that forms a chain in the concept lattice, i.e., a part of the dataset that corresponds to a linear order. To visualize the data in a formal context, Ganter and Glodeanu proposed a biplot based on two ordinal factors. For the biplot to be useful, it is important that these factors comprise as much data points as possible, i.e., that they cover a large part of the incidence relation. In this work, we investigate such ordinal two-factorizations. First, we investigate for formal contexts that omit ordinal two-factorizations the disjointness of the two factors. Then, we show that deciding on the existence of two-factorizations of a given size is an NP-complete problem which makes computing maximal factorizations computationally expensive. Finally, we provide the algorithm Ord2Factor that allows us to compute large ordinal two-factorizations.},
author = {Dürrschnabel, Dominik and Stumme, Gerd},
keywords = {itegpub},
note = {cite arxiv:2304.03338Comment: 14 pages, 6 figures, 2 algorithms},
title = {Maximal Ordinal Two-Factorizations},
year = 2023
}%0 Generic
%1 durrschnabel2023maximal
%A Dürrschnabel, Dominik
%A Stumme, Gerd
%D 2023
%T Maximal Ordinal Two-Factorizations
%U http://arxiv.org/abs/2304.03338
%X Given a formal context, an ordinal factor is a subset of its incidence relation that forms a chain in the concept lattice, i.e., a part of the dataset that corresponds to a linear order. To visualize the data in a formal context, Ganter and Glodeanu proposed a biplot based on two ordinal factors. For the biplot to be useful, it is important that these factors comprise as much data points as possible, i.e., that they cover a large part of the incidence relation. In this work, we investigate such ordinal two-factorizations. First, we investigate for formal contexts that omit ordinal two-factorizations the disjointness of the two factors. Then, we show that deciding on the existence of two-factorizations of a given size is an NP-complete problem which makes computing maximal factorizations computationally expensive. Finally, we provide the algorithm Ord2Factor that allows us to compute large ordinal two-factorizations. - 1.Schäfermeier, B., Hirth, J., Hanika, T.: Research Topic Flows in Co-Authorship Networks. Scientometrics. 128, 5051–5078 (2023). https://doi.org/10.1007/s11192-022-04529-w.In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.
@article{schafermeier2022research,
abstract = {In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.},
author = {Schäfermeier, Bastian and Hirth, Johannes and Hanika, Tom},
journal = {Scientometrics},
keywords = {co-authorships},
month = {09},
number = 9,
pages = {5051--5078},
title = {Research Topic Flows in Co-Authorship Networks},
volume = 128,
year = 2023
}%0 Journal Article
%1 schafermeier2022research
%A Schäfermeier, Bastian
%A Hirth, Johannes
%A Hanika, Tom
%D 2023
%J Scientometrics
%N 9
%P 5051--5078
%R 10.1007/s11192-022-04529-w
%T Research Topic Flows in Co-Authorship Networks
%V 128
%X In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.
2022
- 1.Dürrschnabel, D., Hanika, T., Stubbemann, M.: FCA2VEC: Embedding Techniques for Formal Concept Analysis. In: Missaoui, R., Kwuida, L., and Abdessalem, T. (eds.) Complex Data Analytics with Formal Concept Analysis. pp. 47–74. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-030-93278-7_3.Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding `latent semantic analysis' recent approaches like `word2vec' or `node2vec' are well established tools in this realm. In the present paper we add to this line of research by introducing `fca2vec', a family of embedding techniques for formal concept analysis (FCA). Our investigation contributes to two distinct lines of research. First, we enable the application of FCA notions to large data sets. In particular, we demonstrate how the cover relation of a concept lattice can be retrieved from a computationally feasible embedding. Secondly, we show an enhancement for the classical node2vec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA community.
@inbook{Dürrschnabel2022,
abstract = {Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding `latent semantic analysis' recent approaches like `word2vec' or `node2vec' are well established tools in this realm. In the present paper we add to this line of research by introducing `fca2vec', a family of embedding techniques for formal concept analysis (FCA). Our investigation contributes to two distinct lines of research. First, we enable the application of FCA notions to large data sets. In particular, we demonstrate how the cover relation of a concept lattice can be retrieved from a computationally feasible embedding. Secondly, we show an enhancement for the classical node2vec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA community.},
address = {Cham},
author = {Dürrschnabel, Dominik and Hanika, Tom and Stubbemann, Maximilian},
booktitle = {Complex Data Analytics with Formal Concept Analysis},
editor = {Missaoui, Rokia and Kwuida, L{é}onard and Abdessalem, Talel},
keywords = {fca2vec},
pages = {47--74},
publisher = {Springer International Publishing},
title = {FCA2VEC: Embedding Techniques for Formal Concept Analysis},
year = 2022
}%0 Book Section
%1 Dürrschnabel2022
%A Dürrschnabel, Dominik
%A Hanika, Tom
%A Stubbemann, Maximilian
%B Complex Data Analytics with Formal Concept Analysis
%C Cham
%D 2022
%E Missaoui, Rokia
%E Kwuida, L{é}onard
%E Abdessalem, Talel
%I Springer International Publishing
%P 47--74
%R 10.1007/978-3-030-93278-7_3
%T FCA2VEC: Embedding Techniques for Formal Concept Analysis
%U https://doi.org/10.1007/978-3-030-93278-7_3
%X Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding `latent semantic analysis' recent approaches like `word2vec' or `node2vec' are well established tools in this realm. In the present paper we add to this line of research by introducing `fca2vec', a family of embedding techniques for formal concept analysis (FCA). Our investigation contributes to two distinct lines of research. First, we enable the application of FCA notions to large data sets. In particular, we demonstrate how the cover relation of a concept lattice can be retrieved from a computationally feasible embedding. Secondly, we show an enhancement for the classical node2vec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA community.
%@ 978-3-030-93278-7 - 1.Stubbemann, M., Hanika, T., Schneider, F.M.: Intrinsic Dimension for Large-Scale Geometric Learning, https://arxiv.org/abs/2210.05301, (2022).
@misc{stubbemann2022intrinsic,
author = {Stubbemann, Maximilian and Hanika, Tom and Schneider, Friedrich Martin},
keywords = {outdated},
title = {Intrinsic Dimension for Large-Scale Geometric Learning},
year = 2022
}%0 Generic
%1 stubbemann2022intrinsic
%A Stubbemann, Maximilian
%A Hanika, Tom
%A Schneider, Friedrich Martin
%D 2022
%T Intrinsic Dimension for Large-Scale Geometric Learning
%U https://arxiv.org/abs/2210.05301 - 1.Hanika, T., Hirth, J.: On the lattice of conceptual measurements. Information Sciences. 613, 453–468 (2022). https://doi.org/https://doi.org/10.1016/j.ins.2022.09.005.We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, for which we derive a canonical representation. Moreover, we prove that scale-measures can be lattice ordered using the canonical representation. This enables exploring the set of scale-measures by the use of meet and join operations. Furthermore we show that the lattice of scale-measures is isomorphic to the lattice of sub-closure systems that arises from the original data. Finally, we provide another representation of scale-measures using propositional logic in terms of data set features. Our theoretical findings are discussed by means of examples.
@article{hanika2020lattice,
abstract = {We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, for which we derive a canonical representation. Moreover, we prove that scale-measures can be lattice ordered using the canonical representation. This enables exploring the set of scale-measures by the use of meet and join operations. Furthermore we show that the lattice of scale-measures is isomorphic to the lattice of sub-closure systems that arises from the original data. Finally, we provide another representation of scale-measures using propositional logic in terms of data set features. Our theoretical findings are discussed by means of examples.},
author = {Hanika, Tom and Hirth, Johannes},
journal = {Information Sciences},
keywords = {selected},
pages = {453-468},
title = {On the lattice of conceptual measurements},
volume = 613,
year = 2022
}%0 Journal Article
%1 hanika2020lattice
%A Hanika, Tom
%A Hirth, Johannes
%D 2022
%J Information Sciences
%P 453-468
%R https://doi.org/10.1016/j.ins.2022.09.005
%T On the lattice of conceptual measurements
%U https://www.sciencedirect.com/science/article/pii/S0020025522010489
%V 613
%X We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, for which we derive a canonical representation. Moreover, we prove that scale-measures can be lattice ordered using the canonical representation. This enables exploring the set of scale-measures by the use of meet and join operations. Furthermore we show that the lattice of scale-measures is isomorphic to the lattice of sub-closure systems that arises from the original data. Finally, we provide another representation of scale-measures using propositional logic in terms of data set features. Our theoretical findings are discussed by means of examples. - 1.Hanika, T., Schneider, F.M., Stumme, G.: {Intrinsic dimension of geometric data sets}. Tohoku Mathematical Journal. 74, 23–52 (2022). https://doi.org/10.2748/tmj.20201015a.The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments.
@article{10.2748/tmj.20201015a,
abstract = {The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments.},
author = {Hanika, Tom and Schneider, Friedrich Martin and Stumme, Gerd},
journal = {Tohoku Mathematical Journal},
keywords = {itegpub},
number = 1,
pages = {23 -- 52},
publisher = {Tohoku University, Mathematical Institute},
title = {{Intrinsic dimension of geometric data sets}},
volume = 74,
year = 2022
}%0 Journal Article
%1 10.2748/tmj.20201015a
%A Hanika, Tom
%A Schneider, Friedrich Martin
%A Stumme, Gerd
%D 2022
%I Tohoku University, Mathematical Institute
%J Tohoku Mathematical Journal
%N 1
%P 23 -- 52
%R 10.2748/tmj.20201015a
%T {Intrinsic dimension of geometric data sets}
%U https://doi.org/10.2748/tmj.20201015a
%V 74
%X The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments. - 1.Felde, M., Stumme, G.: Attribute Exploration with Multiple Contradicting Partial Experts. In: Braun, T., Cristea, D., and J{ä}schke, R. (eds.) Graph-Based Representation and Reasoning. pp. 51–65. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-16663-1_5.Attribute exploration is a method from Formal Concept Analysis (FCA) that helps a domain expert discover structural dependencies in knowledge domains which can be represented as formal contexts (cross tables of objects and attributes). In this paper we present an extension of attribute exploration that allows for a group of domain experts and explores their shared views. Each expert has their own view of the domain and the views of multiple experts may contain contradicting information.
@inproceedings{10.1007/978-3-031-16663-1_5,
abstract = {Attribute exploration is a method from Formal Concept Analysis (FCA) that helps a domain expert discover structural dependencies in knowledge domains which can be represented as formal contexts (cross tables of objects and attributes). In this paper we present an extension of attribute exploration that allows for a group of domain experts and explores their shared views. Each expert has their own view of the domain and the views of multiple experts may contain contradicting information.},
address = {Cham},
author = {Felde, Maximilian and Stumme, Gerd},
booktitle = {Graph-Based Representation and Reasoning},
editor = {Braun, Tanya and Cristea, Diana and J{ä}schke, Robert},
keywords = {itegpub},
pages = {51--65},
publisher = {Springer International Publishing},
title = {Attribute Exploration with Multiple Contradicting Partial Experts},
year = 2022
}%0 Conference Paper
%1 10.1007/978-3-031-16663-1_5
%A Felde, Maximilian
%A Stumme, Gerd
%B Graph-Based Representation and Reasoning
%C Cham
%D 2022
%E Braun, Tanya
%E Cristea, Diana
%E J{ä}schke, Robert
%I Springer International Publishing
%P 51--65
%R 10.1007/978-3-031-16663-1_5
%T Attribute Exploration with Multiple Contradicting Partial Experts
%X Attribute exploration is a method from Formal Concept Analysis (FCA) that helps a domain expert discover structural dependencies in knowledge domains which can be represented as formal contexts (cross tables of objects and attributes). In this paper we present an extension of attribute exploration that allows for a group of domain experts and explores their shared views. Each expert has their own view of the domain and the views of multiple experts may contain contradicting information.
%@ 978-3-031-16663-1 - 1.Dürrschnabel, D., Hanika, T., Stumme, G.: Discovering Locally Maximal Bipartite Subgraphs, http://arxiv.org/abs/2211.10446, (2022).Induced bipartite subgraphs of maximal vertex cardinality are an essential concept for the analysis of graphs. Yet, discovering them in large graphs is known to be computationally hard. Therefore, we consider in this work a weaker notion of this problem, where we discard the maximality constraint in favor of inclusion maximality. Thus, we aim to discover locally maximal bipartite subgraphs. For this, we present three heuristic approaches to extract such subgraphs and compare their results to the solutions of the global problem. For the latter, we employ the algorithmic strength of fast SAT-solvers. Our three proposed heuristics are based on a greedy strategy, a simulated annealing approach, and a genetic algorithm, respectively. We evaluate all four algorithms with respect to their time requirement and the vertex cardinality of the discovered bipartite subgraphs on several benchmark datasets
@misc{durrschnabel2022discovering,
abstract = {Induced bipartite subgraphs of maximal vertex cardinality are an essential concept for the analysis of graphs. Yet, discovering them in large graphs is known to be computationally hard. Therefore, we consider in this work a weaker notion of this problem, where we discard the maximality constraint in favor of inclusion maximality. Thus, we aim to discover locally maximal bipartite subgraphs. For this, we present three heuristic approaches to extract such subgraphs and compare their results to the solutions of the global problem. For the latter, we employ the algorithmic strength of fast SAT-solvers. Our three proposed heuristics are based on a greedy strategy, a simulated annealing approach, and a genetic algorithm, respectively. We evaluate all four algorithms with respect to their time requirement and the vertex cardinality of the discovered bipartite subgraphs on several benchmark datasets},
author = {Dürrschnabel, Dominik and Hanika, Tom and Stumme, Gerd},
keywords = {itegpub},
note = {cite arxiv:2211.10446Comment: 12 pages, 3 figures, 3 tables},
title = {Discovering Locally Maximal Bipartite Subgraphs},
year = 2022
}%0 Generic
%1 durrschnabel2022discovering
%A Dürrschnabel, Dominik
%A Hanika, Tom
%A Stumme, Gerd
%D 2022
%T Discovering Locally Maximal Bipartite Subgraphs
%U http://arxiv.org/abs/2211.10446
%X Induced bipartite subgraphs of maximal vertex cardinality are an essential concept for the analysis of graphs. Yet, discovering them in large graphs is known to be computationally hard. Therefore, we consider in this work a weaker notion of this problem, where we discard the maximality constraint in favor of inclusion maximality. Thus, we aim to discover locally maximal bipartite subgraphs. For this, we present three heuristic approaches to extract such subgraphs and compare their results to the solutions of the global problem. For the latter, we employ the algorithmic strength of fast SAT-solvers. Our three proposed heuristics are based on a greedy strategy, a simulated annealing approach, and a genetic algorithm, respectively. We evaluate all four algorithms with respect to their time requirement and the vertex cardinality of the discovered bipartite subgraphs on several benchmark datasets - 1.Hirth, J., Hanika, T.: Formal Conceptual Views in Neural Networks, http://arxiv.org/abs/2209.13517, (2022).Explaining neural network models is a challenging task that remains unsolved in its entirety to this day. This is especially true for high dimensional and complex data. With the present work, we introduce two notions for conceptual views of a neural network, specifically a many-valued and a symbolic view. Both provide novel analysis methods to enable a human AI analyst to grasp deeper insights into the knowledge that is captured by the neurons of a network. We test the conceptual expressivity of our novel views through different experiments on the ImageNet and Fruit-360 data sets. Furthermore, we show to which extent the views allow to quantify the conceptual similarity of different learning architectures. Finally, we demonstrate how conceptual views can be applied for abductive learning of human comprehensible rules from neurons. In summary, with our work, we contribute to the most relevant task of globally explaining neural networks models.
@misc{hirth2022formal,
abstract = {Explaining neural network models is a challenging task that remains unsolved in its entirety to this day. This is especially true for high dimensional and complex data. With the present work, we introduce two notions for conceptual views of a neural network, specifically a many-valued and a symbolic view. Both provide novel analysis methods to enable a human AI analyst to grasp deeper insights into the knowledge that is captured by the neurons of a network. We test the conceptual expressivity of our novel views through different experiments on the ImageNet and Fruit-360 data sets. Furthermore, we show to which extent the views allow to quantify the conceptual similarity of different learning architectures. Finally, we demonstrate how conceptual views can be applied for abductive learning of human comprehensible rules from neurons. In summary, with our work, we contribute to the most relevant task of globally explaining neural networks models.},
author = {Hirth, Johannes and Hanika, Tom},
keywords = {NN},
note = {cite arxiv:2209.13517Comment: 17 pages, 8 figures, 9 tables},
title = {Formal Conceptual Views in Neural Networks},
year = 2022
}%0 Generic
%1 hirth2022formal
%A Hirth, Johannes
%A Hanika, Tom
%D 2022
%T Formal Conceptual Views in Neural Networks
%U http://arxiv.org/abs/2209.13517
%X Explaining neural network models is a challenging task that remains unsolved in its entirety to this day. This is especially true for high dimensional and complex data. With the present work, we introduce two notions for conceptual views of a neural network, specifically a many-valued and a symbolic view. Both provide novel analysis methods to enable a human AI analyst to grasp deeper insights into the knowledge that is captured by the neurons of a network. We test the conceptual expressivity of our novel views through different experiments on the ImageNet and Fruit-360 data sets. Furthermore, we show to which extent the views allow to quantify the conceptual similarity of different learning architectures. Finally, we demonstrate how conceptual views can be applied for abductive learning of human comprehensible rules from neurons. In summary, with our work, we contribute to the most relevant task of globally explaining neural networks models. - 1.Schäfermeier, B., Stumme, G., Hanika, T.: Mapping Research Trajectories, https://arxiv.org/abs/2204.11859, (2022). https://doi.org/10.48550/ARXIV.2204.11859.
@misc{https://doi.org/10.48550/arxiv.2204.11859,
author = {Schäfermeier, Bastian and Stumme, Gerd and Hanika, Tom},
keywords = {trajectory_mapping},
publisher = {arXiv},
title = {Mapping Research Trajectories},
year = 2022
}%0 Generic
%1 https://doi.org/10.48550/arxiv.2204.11859
%A Schäfermeier, Bastian
%A Stumme, Gerd
%A Hanika, Tom
%D 2022
%I arXiv
%R 10.48550/ARXIV.2204.11859
%T Mapping Research Trajectories
%U https://arxiv.org/abs/2204.11859 - 1.D{{ü}}rrschnabel, D., Hanika, T., Stubbemann, M.: {FCA2VEC:} Embedding Techniques for Formal Concept Analysis. In: Missaoui, R., Kwuida, L., and Abdessalem, T. (eds.) Complex Data Analytics with Formal Concept Analysis. pp. 47–74. Springer International Publishing (2022). https://doi.org/10.1007/978-3-030-93278-7_3.
@incollection{DBLP:books/sp/missaoui2022/DurrschnabelHS22,
author = {D{{ü}}rrschnabel, Dominik and Hanika, Tom and Stubbemann, Maximilian},
booktitle = {Complex Data Analytics with Formal Concept Analysis},
editor = {Missaoui, Rokia and Kwuida, L{{é}}onard and Abdessalem, Talel},
keywords = {itegpub},
pages = {47--74},
publisher = {Springer International Publishing},
title = {{FCA2VEC:} Embedding Techniques for Formal Concept Analysis},
year = 2022
}%0 Book Section
%1 DBLP:books/sp/missaoui2022/DurrschnabelHS22
%A D{{ü}}rrschnabel, Dominik
%A Hanika, Tom
%A Stubbemann, Maximilian
%B Complex Data Analytics with Formal Concept Analysis
%D 2022
%E Missaoui, Rokia
%E Kwuida, L{{é}}onard
%E Abdessalem, Talel
%I Springer International Publishing
%P 47--74
%R 10.1007/978-3-030-93278-7_3
%T {FCA2VEC:} Embedding Techniques for Formal Concept Analysis
%U https://doi.org/10.1007/978-3-030-93278-7_3 - 1.Stubbemann, M., Stumme, G.: LG4AV: Combining Language Models and Graph Neural Networks for Author Verification. In: Bouadi, T., Fromont, E., and H{ü}llermeier, E. (eds.) Advances in Intelligent Data Analysis XX. pp. 315–326. Springer International Publishing, Cham (2022).The verification of document authorships is important in various settings. Researchers are for example judged and compared by the amount and impact of their publications and public figures are confronted by their posts on social media. Therefore, it is important that authorship information in frequently used data sets is correct. The question whether a given document is written by a given author is commonly referred to as authorship verification (AV). While AV is a widely investigated problem in general, only few works consider settings where the documents are short and written in a rather uniform style. This makes most approaches impractical for bibliometric data. Here, authorships of scientific publications have to be verified, often with just abstracts and titles available. To this point, we present LG4AV which combines language models and graph neural networks for authorship verification. By directly feeding the available texts in a pre-trained transformer architecture, our model does not need any hand-crafted stylometric features that are not meaningful in scenarios where the writing style is, at least to some extent, standardized. By the incorporation of a graph neural network structure, our model can benefit from relations between authors that are meaningful with respect to the verification process.
@inproceedings{10.1007/978-3-031-01333-1_25,
abstract = {The verification of document authorships is important in various settings. Researchers are for example judged and compared by the amount and impact of their publications and public figures are confronted by their posts on social media. Therefore, it is important that authorship information in frequently used data sets is correct. The question whether a given document is written by a given author is commonly referred to as authorship verification (AV). While AV is a widely investigated problem in general, only few works consider settings where the documents are short and written in a rather uniform style. This makes most approaches impractical for bibliometric data. Here, authorships of scientific publications have to be verified, often with just abstracts and titles available. To this point, we present LG4AV which combines language models and graph neural networks for authorship verification. By directly feeding the available texts in a pre-trained transformer architecture, our model does not need any hand-crafted stylometric features that are not meaningful in scenarios where the writing style is, at least to some extent, standardized. By the incorporation of a graph neural network structure, our model can benefit from relations between authors that are meaningful with respect to the verification process.},
address = {Cham},
author = {Stubbemann, Maximilian and Stumme, Gerd},
booktitle = {Advances in Intelligent Data Analysis XX},
editor = {Bouadi, Tassadit and Fromont, Elisa and H{ü}llermeier, Eyke},
keywords = {itegpub},
pages = {315--326},
publisher = {Springer International Publishing},
title = {LG4AV: Combining Language Models and Graph Neural Networks for Author Verification},
year = 2022
}%0 Conference Paper
%1 10.1007/978-3-031-01333-1_25
%A Stubbemann, Maximilian
%A Stumme, Gerd
%B Advances in Intelligent Data Analysis XX
%C Cham
%D 2022
%E Bouadi, Tassadit
%E Fromont, Elisa
%E H{ü}llermeier, Eyke
%I Springer International Publishing
%P 315--326
%T LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
%U https://link.springer.com/chapter/10.1007/978-3-031-01333-1_25
%X The verification of document authorships is important in various settings. Researchers are for example judged and compared by the amount and impact of their publications and public figures are confronted by their posts on social media. Therefore, it is important that authorship information in frequently used data sets is correct. The question whether a given document is written by a given author is commonly referred to as authorship verification (AV). While AV is a widely investigated problem in general, only few works consider settings where the documents are short and written in a rather uniform style. This makes most approaches impractical for bibliometric data. Here, authorships of scientific publications have to be verified, often with just abstracts and titles available. To this point, we present LG4AV which combines language models and graph neural networks for authorship verification. By directly feeding the available texts in a pre-trained transformer architecture, our model does not need any hand-crafted stylometric features that are not meaningful in scenarios where the writing style is, at least to some extent, standardized. By the incorporation of a graph neural network structure, our model can benefit from relations between authors that are meaningful with respect to the verification process.
%@ 978-3-031-01333-1 - 1.Hanika, T., Hirth, J.: Knowledge cores in large formal contexts. Annals of Mathematics and Artificial Intelligence. 90, 537–567 (2022). https://doi.org/10.1007/s10472-022-09790-6.Knowledge computation tasks, such as computing a base of valid implications, are often infeasible for large data sets. This is in particular true when deriving canonical bases in formal concept analysis (FCA). Therefore, it is necessary to find techniques that on the one hand reduce the data set size, but on the other hand preserve enough structure to extract useful knowledge. Many successful methods are based on random processes to reduce the size of the investigated data set. This, however, makes them hardly interpretable with respect to the discovered knowledge. Other approaches restrict themselves to highly supported subsets and omit rare and (maybe) interesting patterns. An essentially different approach is used in network science, called k-cores. These cores are able to reflect rare patterns, as long as they are well connected within the data set. In this work, we study k-cores in the realm of FCA by exploiting the natural correspondence of bi-partite graphs and formal contexts. This structurally motivated approach leads to a comprehensible extraction of knowledge cores from large formal contexts.
@article{Hanika2022,
abstract = {Knowledge computation tasks, such as computing a base of valid implications, are often infeasible for large data sets. This is in particular true when deriving canonical bases in formal concept analysis (FCA). Therefore, it is necessary to find techniques that on the one hand reduce the data set size, but on the other hand preserve enough structure to extract useful knowledge. Many successful methods are based on random processes to reduce the size of the investigated data set. This, however, makes them hardly interpretable with respect to the discovered knowledge. Other approaches restrict themselves to highly supported subsets and omit rare and (maybe) interesting patterns. An essentially different approach is used in network science, called k-cores. These cores are able to reflect rare patterns, as long as they are well connected within the data set. In this work, we study k-cores in the realm of FCA by exploiting the natural correspondence of bi-partite graphs and formal contexts. This structurally motivated approach leads to a comprehensible extraction of knowledge cores from large formal contexts.},
author = {Hanika, Tom and Hirth, Johannes},
journal = {Annals of Mathematics and Artificial Intelligence},
keywords = {itegpub},
month = {04},
number = 6,
pages = {537--567},
title = {Knowledge cores in large formal contexts},
volume = 90,
year = 2022
}%0 Journal Article
%1 Hanika2022
%A Hanika, Tom
%A Hirth, Johannes
%D 2022
%J Annals of Mathematics and Artificial Intelligence
%N 6
%P 537--567
%R 10.1007/s10472-022-09790-6
%T Knowledge cores in large formal contexts
%U https://doi.org/10.1007/s10472-022-09790-6
%V 90
%X Knowledge computation tasks, such as computing a base of valid implications, are often infeasible for large data sets. This is in particular true when deriving canonical bases in formal concept analysis (FCA). Therefore, it is necessary to find techniques that on the one hand reduce the data set size, but on the other hand preserve enough structure to extract useful knowledge. Many successful methods are based on random processes to reduce the size of the investigated data set. This, however, makes them hardly interpretable with respect to the discovered knowledge. Other approaches restrict themselves to highly supported subsets and omit rare and (maybe) interesting patterns. An essentially different approach is used in network science, called k-cores. These cores are able to reflect rare patterns, as long as they are well connected within the data set. In this work, we study k-cores in the realm of FCA by exploiting the natural correspondence of bi-partite graphs and formal contexts. This structurally motivated approach leads to a comprehensible extraction of knowledge cores from large formal contexts. - 1.Schäfermeier, B., Hirth, J., Hanika, T.: Research Topic Flows in Co-Authorship Networks, https://doi.org/10.1007/s11192-022-04529-w, (2022). https://doi.org/10.1007/s11192-022-04529-w.In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.
@misc{schafermeier2022research,
abstract = {In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.},
author = {Schäfermeier, Bastian and Hirth, Johannes and Hanika, Tom},
journal = {Scientometrics},
keywords = {co-authorships},
month = 10,
title = {Research Topic Flows in Co-Authorship Networks},
year = 2022
}%0 Generic
%1 schafermeier2022research
%A Schäfermeier, Bastian
%A Hirth, Johannes
%A Hanika, Tom
%D 2022
%J Scientometrics
%R 10.1007/s11192-022-04529-w
%T Research Topic Flows in Co-Authorship Networks
%U https://doi.org/10.1007/s11192-022-04529-w
%X In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields. - 1.Felde, M., Koyda, M.: Interval-Dismantling for Lattices, https://arxiv.org/abs/2208.01479, (2022). https://doi.org/10.48550/arXiv.2208.01479.Dismantling allows for the removal of elements of a set, or in our case lattice, without disturbing the remaining structure. In this paper we have extended the notion of dismantling by single elements to the dismantling by intervals in a lattice. We utilize theory from Formal Concept Analysis (FCA) to show that lattices dismantled by intervals correspond to closed subrelations in the respective formal context, and that there exists a unique kernel with respect to dismantling by intervals. Furthermore, we show that dismantling intervals can be identified directly in the formal context utilizing a characterization via arrow relations and provide an algorithm to compute all dismantling intervals.
@preprint{felde2022intervaldismantling,
abstract = {Dismantling allows for the removal of elements of a set, or in our case lattice, without disturbing the remaining structure. In this paper we have extended the notion of dismantling by single elements to the dismantling by intervals in a lattice. We utilize theory from Formal Concept Analysis (FCA) to show that lattices dismantled by intervals correspond to closed subrelations in the respective formal context, and that there exists a unique kernel with respect to dismantling by intervals. Furthermore, we show that dismantling intervals can be identified directly in the formal context utilizing a characterization via arrow relations and provide an algorithm to compute all dismantling intervals.},
author = {Felde, Maximilian and Koyda, Maren},
keywords = {myown},
note = {cite arxiv:2208.01479Comment: 12 pages, 5 figures, 1 algorithm},
title = {Interval-Dismantling for Lattices},
year = 2022
}%0 Generic
%1 felde2022intervaldismantling
%A Felde, Maximilian
%A Koyda, Maren
%D 2022
%R 10.48550/arXiv.2208.01479
%T Interval-Dismantling for Lattices
%U https://arxiv.org/abs/2208.01479
%X Dismantling allows for the removal of elements of a set, or in our case lattice, without disturbing the remaining structure. In this paper we have extended the notion of dismantling by single elements to the dismantling by intervals in a lattice. We utilize theory from Formal Concept Analysis (FCA) to show that lattices dismantled by intervals correspond to closed subrelations in the respective formal context, and that there exists a unique kernel with respect to dismantling by intervals. Furthermore, we show that dismantling intervals can be identified directly in the formal context utilizing a characterization via arrow relations and provide an algorithm to compute all dismantling intervals.
2021
- 1.Schäfermeier, B., Stumme, G., Hanika, T.: Towards Explainable Scientific Venue Recommendations, http://arxiv.org/abs/2109.11343, (2021).Selecting the best scientific venue (i.e., conference/journal) for the submission of a research article constitutes a multifaceted challenge. Important aspects to consider are the suitability of research topics, a venue's prestige, and the probability of acceptance. The selection problem is exacerbated through the continuous emergence of additional venues. Previously proposed approaches for supporting authors in this process rely on complex recommender systems, e.g., based on Word2Vec or TextCNN. These, however, often elude an explanation for their recommendations. In this work, we propose an unsophisticated method that advances the state-of-the-art in two aspects: First, we enhance the interpretability of recommendations through non-negative matrix factorization based topic models; Second, we surprisingly can obtain competitive recommendation performance while using simpler learning methods.
@misc{schafermeier2021towards,
abstract = {Selecting the best scientific venue (i.e., conference/journal) for the submission of a research article constitutes a multifaceted challenge. Important aspects to consider are the suitability of research topics, a venue's prestige, and the probability of acceptance. The selection problem is exacerbated through the continuous emergence of additional venues. Previously proposed approaches for supporting authors in this process rely on complex recommender systems, e.g., based on Word2Vec or TextCNN. These, however, often elude an explanation for their recommendations. In this work, we propose an unsophisticated method that advances the state-of-the-art in two aspects: First, we enhance the interpretability of recommendations through non-negative matrix factorization based topic models; Second, we surprisingly can obtain competitive recommendation performance while using simpler learning methods.},
author = {Schäfermeier, Bastian and Stumme, Gerd and Hanika, Tom},
keywords = {venue_recommendations},
note = {cite arxiv:2109.11343},
title = {Towards Explainable Scientific Venue Recommendations},
year = 2021
}%0 Generic
%1 schafermeier2021towards
%A Schäfermeier, Bastian
%A Stumme, Gerd
%A Hanika, Tom
%D 2021
%T Towards Explainable Scientific Venue Recommendations
%U http://arxiv.org/abs/2109.11343
%X Selecting the best scientific venue (i.e., conference/journal) for the submission of a research article constitutes a multifaceted challenge. Important aspects to consider are the suitability of research topics, a venue's prestige, and the probability of acceptance. The selection problem is exacerbated through the continuous emergence of additional venues. Previously proposed approaches for supporting authors in this process rely on complex recommender systems, e.g., based on Word2Vec or TextCNN. These, however, often elude an explanation for their recommendations. In this work, we propose an unsophisticated method that advances the state-of-the-art in two aspects: First, we enhance the interpretability of recommendations through non-negative matrix factorization based topic models; Second, we surprisingly can obtain competitive recommendation performance while using simpler learning methods. - 1.D{ü}rrschnabel, D., Stumme, G.: Force-Directed Layout of Order Diagrams Using Dimensional Reduction. In: Braud, A., Buzmakov, A., Hanika, T., and Le Ber, F. (eds.) Formal Concept Analysis. pp. 224–240. Springer International Publishing, Cham (2021).Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity.
@inproceedings{10.1007/978-3-030-77867-5_14,
abstract = {Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity.},
address = {Cham},
author = {D{ü}rrschnabel, Dominik and Stumme, Gerd},
booktitle = {Formal Concept Analysis},
editor = {Braud, Agn{è}s and Buzmakov, Aleksey and Hanika, Tom and Le Ber, Florence},
keywords = {itegpub},
pages = {224--240},
publisher = {Springer International Publishing},
title = {Force-Directed Layout of Order Diagrams Using Dimensional Reduction},
year = 2021
}%0 Conference Paper
%1 10.1007/978-3-030-77867-5_14
%A D{ü}rrschnabel, Dominik
%A Stumme, Gerd
%B Formal Concept Analysis
%C Cham
%D 2021
%E Braud, Agn{è}s
%E Buzmakov, Aleksey
%E Hanika, Tom
%E Le Ber, Florence
%I Springer International Publishing
%P 224--240
%T Force-Directed Layout of Order Diagrams Using Dimensional Reduction
%X Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity.
%@ 978-3-030-77867-5 - 1.Braun, T., Gehrke, M., Hanika, T., Hernandez, N. eds.: Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings. Springer (2021). https://doi.org/10.1007/978-3-030-86982-3.
@proceedings{DBLP:conf/iccs/2021,
editor = {Braun, Tanya and Gehrke, Marcel and Hanika, Tom and Hernandez, Nathalie},
keywords = {itegpub},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings},
volume = 12879,
year = 2021
}%0 Conference Proceedings
%1 DBLP:conf/iccs/2021
%B Lecture Notes in Computer Science
%D 2021
%E Braun, Tanya
%E Gehrke, Marcel
%E Hanika, Tom
%E Hernandez, Nathalie
%I Springer
%R 10.1007/978-3-030-86982-3
%T Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings
%U https://doi.org/10.1007/978-3-030-86982-3
%V 12879
%@ 978-3-030-86981-6 - 1.Schaefermeier, B., Stumme, G., Hanika, T.: Topological Indoor Mapping through WiFi Signals. (2021).The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping. In particular, no additional infrastructure is required. Previous approaches in this field were, however, often hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. These represent discrete locations, such as rooms, and their relations, e.g., distances and transition frequencies. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering. It can be used in settings where users carry mobile devices and follow their normal routine. We aim for applications in short-lived indoor events such as conferences.
@article{schaefermeier2021topological,
abstract = {The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping. In particular, no additional infrastructure is required. Previous approaches in this field were, however, often hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. These represent discrete locations, such as rooms, and their relations, e.g., distances and transition frequencies. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering. It can be used in settings where users carry mobile devices and follow their normal routine. We aim for applications in short-lived indoor events such as conferences.},
author = {Schaefermeier, Bastian and Stumme, Gerd and Hanika, Tom},
keywords = {itegpub},
note = {cite arxiv:2106.09789Comment: 18 pages},
title = {Topological Indoor Mapping through WiFi Signals},
year = 2021
}%0 Journal Article
%1 schaefermeier2021topological
%A Schaefermeier, Bastian
%A Stumme, Gerd
%A Hanika, Tom
%D 2021
%T Topological Indoor Mapping through WiFi Signals
%U http://arxiv.org/abs/2106.09789
%X The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping. In particular, no additional infrastructure is required. Previous approaches in this field were, however, often hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. These represent discrete locations, such as rooms, and their relations, e.g., distances and transition frequencies. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering. It can be used in settings where users carry mobile devices and follow their normal routine. We aim for applications in short-lived indoor events such as conferences. - 1.Stubbemann, M., Stumme, G.: The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks. arXiv preprint arXiv:2110.13774. (2021).
@article{stubbemann2021mont,
author = {Stubbemann, Maximilian and Stumme, Gerd},
journal = {arXiv preprint arXiv:2110.13774},
keywords = {itegpub},
title = {The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks},
year = 2021
}%0 Journal Article
%1 stubbemann2021mont
%A Stubbemann, Maximilian
%A Stumme, Gerd
%D 2021
%J arXiv preprint arXiv:2110.13774
%T The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks - 1.Schaefermeier, B., Stumme, G., Hanika, T.: Topic space trajectories. Scientometrics. 126, 5759–5795 (2021). https://doi.org/10.1007/s11192-021-03931-0.The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues. In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work. An advantage in these applications over previous methods lies in the good interpretability of the results obtained through our methods.
@article{schafermeier2020topic,
abstract = {The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues. In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work. An advantage in these applications over previous methods lies in the good interpretability of the results obtained through our methods.},
author = {Schaefermeier, Bastian and Stumme, Gerd and Hanika, Tom},
journal = {Scientometrics},
keywords = 2021,
month = {07},
number = 7,
pages = {5759-5795},
publisher = {Springer},
title = {Topic space trajectories},
volume = 126,
year = 2021
}%0 Journal Article
%1 schafermeier2020topic
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%A Stumme, Gerd
%A Hanika, Tom
%D 2021
%I Springer
%J Scientometrics
%N 7
%P 5759-5795
%R 10.1007/s11192-021-03931-0
%T Topic space trajectories
%U https://doi.org/10.1007/s11192-021-03931-0
%V 126
%X The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues. In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work. An advantage in these applications over previous methods lies in the good interpretability of the results obtained through our methods. - 1.Koopmann, T., Stubbemann, M., Kapa, M., Paris, M., Buenstorf, G., Hanika, T., Hotho, A., Jäschke, R., Stumme, G.: Proximity Dimensions and the Emergence of Collaboration: A HypTrails Study on German AI Research. Scientometrics. 126, 9847–9868 (2021). https://doi.org/https://doi.org/10.1007/s11192-021-03922-1.
@article{koopmann2021proximity,
author = {Koopmann, T. and Stubbemann, M. and Kapa, M. and Paris, M. and Buenstorf, G. and Hanika, T. and Hotho, A. and Jäschke, R. and Stumme, G.},
journal = {Scientometrics},
keywords = {itegpub},
month = {03},
number = 12,
pages = {9847–9868},
title = {Proximity Dimensions and the Emergence of Collaboration: A HypTrails Study on German AI Research},
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year = 2021
}%0 Journal Article
%1 koopmann2021proximity
%A Koopmann, T.
%A Stubbemann, M.
%A Kapa, M.
%A Paris, M.
%A Buenstorf, G.
%A Hanika, T.
%A Hotho, A.
%A Jäschke, R.
%A Stumme, G.
%D 2021
%J Scientometrics
%N 12
%P 9847–9868
%R https://doi.org/10.1007/s11192-021-03922-1
%T Proximity Dimensions and the Emergence of Collaboration: A HypTrails Study on German AI Research
%U https://link.springer.com/article/10.1007/s11192-021-03922-1
%V 126 - 1.Stubbemann, L., Dürrschnabel, D., Refflinghaus, R.: Neural Networks for Semantic Gaze Analysis in XR Settings. In: Bulling, A., Huckauf, A., Gellersen, H., Weiskopf, D., Bace, M., Hirzle, T., Alt, F., Pfeiffer, T., Bednarik, R., Krejtz, K., Blascheck, T., Burch, M., Kiefer, P., Dodd, M.D., and Sharif, B. (eds.) ETRA ’21 Full Papers: ACM Symposium on Eye Tracking Research and Applications. {ACM} (2021). https://doi.org/10.1145/3448017.3457380.
@inproceedings{Stubbemann_2021,
author = {Stubbemann, Lena and Dürrschnabel, Dominik and Refflinghaus, Robert},
booktitle = {ETRA '21 Full Papers: ACM Symposium on Eye Tracking Research and Applications},
editor = {Bulling, Andreas and Huckauf, Anke and Gellersen, Hans and Weiskopf, Daniel and Bace, Mihai and Hirzle, Teresa and Alt, Florian and Pfeiffer, Thies and Bednarik, Roman and Krejtz, Krzysztof and Blascheck, Tanja and Burch, Michael and Kiefer, Peter and Dodd, Michael D. and Sharif, Bonita},
keywords = {itegpub},
month = {05},
publisher = {{ACM}},
title = {Neural Networks for Semantic Gaze Analysis in XR Settings},
year = 2021
}%0 Conference Paper
%1 Stubbemann_2021
%A Stubbemann, Lena
%A Dürrschnabel, Dominik
%A Refflinghaus, Robert
%B ETRA '21 Full Papers: ACM Symposium on Eye Tracking Research and Applications
%D 2021
%E Bulling, Andreas
%E Huckauf, Anke
%E Gellersen, Hans
%E Weiskopf, Daniel
%E Bace, Mihai
%E Hirzle, Teresa
%E Alt, Florian
%E Pfeiffer, Thies
%E Bednarik, Roman
%E Krejtz, Krzysztof
%E Blascheck, Tanja
%E Burch, Michael
%E Kiefer, Peter
%E Dodd, Michael D.
%E Sharif, Bonita
%I {ACM}
%R 10.1145/3448017.3457380
%T Neural Networks for Semantic Gaze Analysis in XR Settings
%U https://doi.org/10.1145%2F3448017.3457380
%@ 978-1-4503-8344-8 - 1.Draude, C., Gruhl, C., Hornung, G., Kropf, J., Lamla, J., Leimeister, J.M., Sick, B., Stumme, G.: Social Machines. Informatik Spektrum. (2021). https://doi.org/10.1007/s00287-021-01421-4.
@article{2021,
author = {Draude, Claude and Gruhl, Christian and Hornung, Gerrit and Kropf, Jonathan and Lamla, Jörn and Leimeister, Jan Marco and Sick, Bernhard and Stumme, Gerd},
journal = {Informatik Spektrum},
keywords = {itegpub},
month = 11,
title = {Social Machines},
year = 2021
}%0 Journal Article
%1 2021
%A Draude, Claude
%A Gruhl, Christian
%A Hornung, Gerrit
%A Kropf, Jonathan
%A Lamla, Jörn
%A Leimeister, Jan Marco
%A Sick, Bernhard
%A Stumme, Gerd
%D 2021
%J Informatik Spektrum
%R 10.1007/s00287-021-01421-4
%T Social Machines
%U https://doi.org/10.1007%2Fs00287-021-01421-4 - 1.Felde, M., Stumme, G.: Triadic Exploration and Exploration with Multiple Experts. In: Braud, A., Buzmakov, A., Hanika, T., and Le Ber, F. (eds.) Formal Concept Analysis. pp. 175–191. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-77867-5_11.Formal Concept Analysis (FCA) provides a method called attribute exploration which helps a domain expert discover structural dependencies in knowledge domains that can be represented by a formal context (a cross table of objects and attributes). Triadic Concept Analysis is an extension of FCA that incorporates the notion of conditions. Many extensions and variants of attribute exploration have been studied but only few attempts at incorporating multiple experts have been made. In this paper we present triadic exploration based on Triadic Concept Analysis to explore conditional attribute implications in a triadic domain. We then adapt this approach to formulate attribute exploration with multiple experts that have different views on a domain.
@inproceedings{10.1007/978-3-030-77867-5_11,
abstract = {Formal Concept Analysis (FCA) provides a method called attribute exploration which helps a domain expert discover structural dependencies in knowledge domains that can be represented by a formal context (a cross table of objects and attributes). Triadic Concept Analysis is an extension of FCA that incorporates the notion of conditions. Many extensions and variants of attribute exploration have been studied but only few attempts at incorporating multiple experts have been made. In this paper we present triadic exploration based on Triadic Concept Analysis to explore conditional attribute implications in a triadic domain. We then adapt this approach to formulate attribute exploration with multiple experts that have different views on a domain.},
address = {Cham},
author = {Felde, Maximilian and Stumme, Gerd},
booktitle = {Formal Concept Analysis},
editor = {Braud, Agn{è}s and Buzmakov, Aleksey and Hanika, Tom and Le Ber, Florence},
keywords = 2021,
pages = {175--191},
publisher = {Springer International Publishing},
title = {Triadic Exploration and Exploration with Multiple Experts},
year = 2021
}%0 Conference Paper
%1 10.1007/978-3-030-77867-5_11
%A Felde, Maximilian
%A Stumme, Gerd
%B Formal Concept Analysis
%C Cham
%D 2021
%E Braud, Agn{è}s
%E Buzmakov, Aleksey
%E Hanika, Tom
%E Le Ber, Florence
%I Springer International Publishing
%P 175--191
%R 10.1007/978-3-030-77867-5_11
%T Triadic Exploration and Exploration with Multiple Experts
%X Formal Concept Analysis (FCA) provides a method called attribute exploration which helps a domain expert discover structural dependencies in knowledge domains that can be represented by a formal context (a cross table of objects and attributes). Triadic Concept Analysis is an extension of FCA that incorporates the notion of conditions. Many extensions and variants of attribute exploration have been studied but only few attempts at incorporating multiple experts have been made. In this paper we present triadic exploration based on Triadic Concept Analysis to explore conditional attribute implications in a triadic domain. We then adapt this approach to formulate attribute exploration with multiple experts that have different views on a domain.
%@ 978-3-030-77867-5 - 1.Koyda, M., Stumme, G.: Boolean Substructures in Formal Concept Analysis. In: ICFCA: International Conference on Formal Concept Analysis. pp. 38–53. Springer (2021).
@conference{koyda2021boolean,
author = {Koyda, Maren and Stumme, Gerd},
booktitle = {Formal Concept Analysis - 16th International Conference, ICFCA 2021, Strasbourg, France, June 29 – July 2, 2021, Proceedings},
journal = {ICFCA: International Conference on Formal Concept Analysis},
keywords = {itegpub},
pages = {38-53},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Boolean Substructures in Formal Concept Analysis},
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}%0 Generic
%1 koyda2021boolean
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%I Springer
%J ICFCA: International Conference on Formal Concept Analysis
%P 38-53
%T Boolean Substructures in Formal Concept Analysis
%@ 978-3-030-77866-8 - 1.Hanika, T., Hirth, J.: Exploring Scale-Measures of Data Sets. In: Braud, A., Buzmakov, A., Hanika, T., and Ber, F.L. (eds.) Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings. pp. 261–269. Springer (2021). https://doi.org/10.1007/978-3-030-77867-5_17.
@inproceedings{DBLP:conf/icfca/HanikaH21,
author = {Hanika, Tom and Hirth, Johannes},
booktitle = {Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings},
editor = {Braud, Agn{{è}}s and Buzmakov, Aleksey and Hanika, Tom and Ber, Florence Le},
keywords = {itegpub},
pages = {261--269},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Exploring Scale-Measures of Data Sets},
volume = 12733,
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}%0 Conference Paper
%1 DBLP:conf/icfca/HanikaH21
%A Hanika, Tom
%A Hirth, Johannes
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%D 2021
%E Braud, Agn{{è}}s
%E Buzmakov, Aleksey
%E Hanika, Tom
%E Ber, Florence Le
%I Springer
%P 261--269
%R 10.1007/978-3-030-77867-5_17
%T Exploring Scale-Measures of Data Sets
%U https://doi.org/10.1007/978-3-030-77867-5_17
%V 12733 - 1.Dürrschnabel, D., Stumme, G.: Force-Directed Layout of Order Diagrams Using Dimensional Reduction. In: Braud, A., Buzmakov, A., Hanika, T., and Le Ber, F. (eds.) Formal Concept Analysis. pp. 224–240. Springer International Publishing, Cham (2021).Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity.
@inproceedings{10.1007/978-3-030-77867-5_14,
abstract = {Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity.},
address = {Cham},
author = {Dürrschnabel, Dominik and Stumme, Gerd},
booktitle = {Formal Concept Analysis},
editor = {Braud, Agn{è}s and Buzmakov, Aleksey and Hanika, Tom and Le Ber, Florence},
keywords = {itegpub},
pages = {224--240},
publisher = {Springer International Publishing},
title = {Force-Directed Layout of Order Diagrams Using Dimensional Reduction},
year = 2021
}%0 Conference Paper
%1 10.1007/978-3-030-77867-5_14
%A Dürrschnabel, Dominik
%A Stumme, Gerd
%B Formal Concept Analysis
%C Cham
%D 2021
%E Braud, Agn{è}s
%E Buzmakov, Aleksey
%E Hanika, Tom
%E Le Ber, Florence
%I Springer International Publishing
%P 224--240
%T Force-Directed Layout of Order Diagrams Using Dimensional Reduction
%X Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity.
%@ 978-3-030-77867-5 - 1.Hanika, T., Hirth, J.: Quantifying the Conceptual Error in Dimensionality Reduction. In: Braun, T., Gehrke, M., Hanika, T., and Hernandez, N. (eds.) Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, ICCS 2021, Virtual Event, September 20-22, 2021, Proceedings. pp. 105–118. Springer (2021). https://doi.org/10.1007/978-3-030-86982-3_8.
@inproceedings{DBLP:conf/iccs/HanikaH21,
author = {Hanika, Tom and Hirth, Johannes},
booktitle = {Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, ICCS 2021, Virtual Event, September 20-22, 2021, Proceedings},
editor = {Braun, Tanya and Gehrke, Marcel and Hanika, Tom and Hernandez, Nathalie},
keywords = {selected},
pages = {105--118},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Quantifying the Conceptual Error in Dimensionality Reduction},
volume = 12879,
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}%0 Conference Paper
%1 DBLP:conf/iccs/HanikaH21
%A Hanika, Tom
%A Hirth, Johannes
%B Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, ICCS 2021, Virtual Event, September 20-22, 2021, Proceedings
%D 2021
%E Braun, Tanya
%E Gehrke, Marcel
%E Hanika, Tom
%E Hernandez, Nathalie
%I Springer
%P 105--118
%R 10.1007/978-3-030-86982-3_8
%T Quantifying the Conceptual Error in Dimensionality Reduction
%U https://doi.org/10.1007/978-3-030-86982-3_8
%V 12879 - 1.Stubbemann, M., Stumme, G.: LG4AV: Combining Language Models and Graph Neural Networks for Author Verification. (2021).
@article{stubbemann2021lg4av,
author = {Stubbemann, Maximilian and Stumme, Gerd},
keywords = {itegpub},
title = {LG4AV: Combining Language Models and Graph Neural Networks for Author Verification},
year = 2021
}%0 Journal Article
%1 stubbemann2021lg4av
%A Stubbemann, Maximilian
%A Stumme, Gerd
%D 2021
%T LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
%U https://arxiv.org/abs/2109.01479 - 1.Braud, A., Buzmakov, A., Hanika, T., Ber, F.L. eds.: Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings. Springer (2021). https://doi.org/10.1007/978-3-030-77867-5.
@proceedings{DBLP:conf/icfca/2021,
editor = {Braud, Agn{{è}}s and Buzmakov, Aleksey and Hanika, Tom and Ber, Florence Le},
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publisher = {Springer},
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%B Lecture Notes in Computer Science
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%E Braud, Agn{{è}}s
%E Buzmakov, Aleksey
%E Hanika, Tom
%E Ber, Florence Le
%I Springer
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%T Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings
%U https://doi.org/10.1007/978-3-030-77867-5
%V 12733
%@ 978-3-030-77866-8 - 1.Dürrschnabel, D., Hanika, T., Stubbemann, M.: FCA2VEC: Embedding Techniques for Formal Concept Analysis. Presented at the (2021).
@inbook{durrschnabel2021fca2vec,
author = {Dürrschnabel, Dominik and Hanika, Tom and Stubbemann, Maximilian},
keywords = {fca2vec},
title = {FCA2VEC: Embedding Techniques for Formal Concept Analysis},
year = 2021
}%0 Book Section
%1 durrschnabel2021fca2vec
%A Dürrschnabel, Dominik
%A Hanika, Tom
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%T FCA2VEC: Embedding Techniques for Formal Concept Analysis - 1.Dürrschnabel, D., Koyda, M., Stumme, G.: Attribute Selection Using Contranominal Scales. In: Braun, T., Gehrke, M., Hanika, T., and Hernandez, N. (eds.) Graph-Based Representation and Reasoning. pp. 127–141. Springer International Publishing, Cham (2021).Formal Concept Analysis (FCA) allows to analyze binary data by deriving concepts and ordering them in lattices. One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural properties. The size of such a lattice depends on the number of subcontexts in the corresponding formal context that are isomorphic to a contranominal scale of high dimension. In this work, we propose the algorithm ContraFinder that enables the computation of all contranominal scales of a given formal context. Leveraging this algorithm, we introduce {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting, a novel approach in order to decrease the number of contranominal scales in a formal context by the selection of an appropriate attribute subset. We demonstrate that {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting a context reduces the size of the hereby emerging sub-semilattice and that the implication set is restricted to meaningful implications. This is evaluated with respect to its associated knowledge by means of a classification task. Hence, our proposed technique strongly improves understandability while preserving important conceptual structures.
@inproceedings{10.1007/978-3-030-86982-3_10,
abstract = {Formal Concept Analysis (FCA) allows to analyze binary data by deriving concepts and ordering them in lattices. One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural properties. The size of such a lattice depends on the number of subcontexts in the corresponding formal context that are isomorphic to a contranominal scale of high dimension. In this work, we propose the algorithm ContraFinder that enables the computation of all contranominal scales of a given formal context. Leveraging this algorithm, we introduce {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting, a novel approach in order to decrease the number of contranominal scales in a formal context by the selection of an appropriate attribute subset. We demonstrate that {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting a context reduces the size of the hereby emerging sub-semilattice and that the implication set is restricted to meaningful implications. This is evaluated with respect to its associated knowledge by means of a classification task. Hence, our proposed technique strongly improves understandability while preserving important conceptual structures.},
address = {Cham},
author = {Dürrschnabel, Dominik and Koyda, Maren and Stumme, Gerd},
booktitle = {Graph-Based Representation and Reasoning},
editor = {Braun, Tanya and Gehrke, Marcel and Hanika, Tom and Hernandez, Nathalie},
keywords = {itegpub},
pages = {127--141},
publisher = {Springer International Publishing},
title = {Attribute Selection Using Contranominal Scales},
year = 2021
}%0 Conference Paper
%1 10.1007/978-3-030-86982-3_10
%A Dürrschnabel, Dominik
%A Koyda, Maren
%A Stumme, Gerd
%B Graph-Based Representation and Reasoning
%C Cham
%D 2021
%E Braun, Tanya
%E Gehrke, Marcel
%E Hanika, Tom
%E Hernandez, Nathalie
%I Springer International Publishing
%P 127--141
%T Attribute Selection Using Contranominal Scales
%X Formal Concept Analysis (FCA) allows to analyze binary data by deriving concepts and ordering them in lattices. One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural properties. The size of such a lattice depends on the number of subcontexts in the corresponding formal context that are isomorphic to a contranominal scale of high dimension. In this work, we propose the algorithm ContraFinder that enables the computation of all contranominal scales of a given formal context. Leveraging this algorithm, we introduce {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting, a novel approach in order to decrease the number of contranominal scales in a formal context by the selection of an appropriate attribute subset. We demonstrate that {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting a context reduces the size of the hereby emerging sub-semilattice and that the implication set is restricted to meaningful implications. This is evaluated with respect to its associated knowledge by means of a classification task. Hence, our proposed technique strongly improves understandability while preserving important conceptual structures.
%@ 978-3-030-86982-3 - 1.D{ü}rrschnabel, D., Koyda, M., Stumme, G.: Attribute Selection Using Contranominal Scales. In: Braun, T., Gehrke, M., Hanika, T., and Hernandez, N. (eds.) Graph-Based Representation and Reasoning. pp. 127–141. Springer International Publishing, Cham (2021).Formal Concept Analysis (FCA) allows to analyze binary data by deriving concepts and ordering them in lattices. One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural properties. The size of such a lattice depends on the number of subcontexts in the corresponding formal context that are isomorphic to a contranominal scale of high dimension. In this work, we propose the algorithm ContraFinder that enables the computation of all contranominal scales of a given formal context. Leveraging this algorithm, we introduce {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting, a novel approach in order to decrease the number of contranominal scales in a formal context by the selection of an appropriate attribute subset. We demonstrate that {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting a context reduces the size of the hereby emerging sub-semilattice and that the implication set is restricted to meaningful implications. This is evaluated with respect to its associated knowledge by means of a classification task. Hence, our proposed technique strongly improves understandability while preserving important conceptual structures.
@inproceedings{10.1007/978-3-030-86982-3_10,
abstract = {Formal Concept Analysis (FCA) allows to analyze binary data by deriving concepts and ordering them in lattices. One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural properties. The size of such a lattice depends on the number of subcontexts in the corresponding formal context that are isomorphic to a contranominal scale of high dimension. In this work, we propose the algorithm ContraFinder that enables the computation of all contranominal scales of a given formal context. Leveraging this algorithm, we introduce {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting, a novel approach in order to decrease the number of contranominal scales in a formal context by the selection of an appropriate attribute subset. We demonstrate that {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting a context reduces the size of the hereby emerging sub-semilattice and that the implication set is restricted to meaningful implications. This is evaluated with respect to its associated knowledge by means of a classification task. Hence, our proposed technique strongly improves understandability while preserving important conceptual structures.},
address = {Cham},
author = {D{ü}rrschnabel, Dominik and Koyda, Maren and Stumme, Gerd},
booktitle = {Graph-Based Representation and Reasoning},
editor = {Braun, Tanya and Gehrke, Marcel and Hanika, Tom and Hernandez, Nathalie},
keywords = 2021,
pages = {127--141},
publisher = {Springer International Publishing},
title = {Attribute Selection Using Contranominal Scales},
year = 2021
}%0 Conference Paper
%1 10.1007/978-3-030-86982-3_10
%A D{ü}rrschnabel, Dominik
%A Koyda, Maren
%A Stumme, Gerd
%B Graph-Based Representation and Reasoning
%C Cham
%D 2021
%E Braun, Tanya
%E Gehrke, Marcel
%E Hanika, Tom
%E Hernandez, Nathalie
%I Springer International Publishing
%P 127--141
%T Attribute Selection Using Contranominal Scales
%X Formal Concept Analysis (FCA) allows to analyze binary data by deriving concepts and ordering them in lattices. One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural properties. The size of such a lattice depends on the number of subcontexts in the corresponding formal context that are isomorphic to a contranominal scale of high dimension. In this work, we propose the algorithm ContraFinder that enables the computation of all contranominal scales of a given formal context. Leveraging this algorithm, we introduce {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting, a novel approach in order to decrease the number of contranominal scales in a formal context by the selection of an appropriate attribute subset. We demonstrate that {\$}{\$}{\backslash}delta {\$}{\$}$\delta$-adjusting a context reduces the size of the hereby emerging sub-semilattice and that the implication set is restricted to meaningful implications. This is evaluated with respect to its associated knowledge by means of a classification task. Hence, our proposed technique strongly improves understandability while preserving important conceptual structures.
%@ 978-3-030-86982-3
2020
- 1.Felde, M., Hanika, T., Stumme, G.: Null Models for Formal Contexts. Information. 11, 135 (2020).
@article{felde2020null,
author = {Felde, Maximilian and Hanika, Tom and Stumme, Gerd},
journal = {Information},
keywords = {itegpub},
number = 3,
pages = 135,
publisher = {Multidisciplinary Digital Publishing Institute},
title = {Null Models for Formal Contexts},
volume = 11,
year = 2020
}%0 Journal Article
%1 felde2020null
%A Felde, Maximilian
%A Hanika, Tom
%A Stumme, Gerd
%D 2020
%I Multidisciplinary Digital Publishing Institute
%J Information
%N 3
%P 135
%T Null Models for Formal Contexts
%U https://www.mdpi.com/2078-2489/11/3/135
%V 11 - 1.Hanika, T., Schneider, F.M., Stumme, G.: Intrinsic Dimension of Geometric Data Sets. Accepted for publication in: Tohoku Mathematical Journal. (2020).The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our mathematical model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments.
@article{hanika2018intrinsic,
abstract = {The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our mathematical model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments.},
author = {Hanika, Tom and Schneider, Friedrich Martin and Stumme, Gerd},
journal = {Accepted for publication in: Tohoku Mathematical Journal},
keywords = {itegpub},
note = {cite arxiv:1801.07985Comment: v2: completely rewritten 28 pages, 3 figures, 2 tables},
title = {Intrinsic Dimension of Geometric Data Sets},
year = 2020
}%0 Journal Article
%1 hanika2018intrinsic
%A Hanika, Tom
%A Schneider, Friedrich Martin
%A Stumme, Gerd
%D 2020
%J Accepted for publication in: Tohoku Mathematical Journal
%T Intrinsic Dimension of Geometric Data Sets
%U http://arxiv.org/abs/1801.07985
%X The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our mathematical model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments. - 1.Stubbemann, M., Hanika, T., Stumme, G.: Orometric Methods in Bounded Metric Data. In: Berthold, M.R., Feelders, A., and Krempl, G. (eds.) Advances in Intelligent Data Analysis {XVIII} - 18th International Symposium on Intelligent Data Analysis, {IDA} 2020, Konstanz, Germany, April 27-29, 2020, Proceedings. pp. 496–508. Springer (2020). https://doi.org/10.1007/978-3-030-44584-3_39.
@inproceedings{DBLP:conf/ida/StubbemannHS20,
author = {Stubbemann, Maximilian and Hanika, Tom and Stumme, Gerd},
booktitle = {Advances in Intelligent Data Analysis {XVIII} - 18th International Symposium on Intelligent Data Analysis, {IDA} 2020, Konstanz, Germany, April 27-29, 2020, Proceedings},
editor = {Berthold, Michael R. and Feelders, Ad and Krempl, Georg},
keywords = {itegpub},
pages = {496--508},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Orometric Methods in Bounded Metric Data},
volume = 12080,
year = 2020
}%0 Conference Paper
%1 DBLP:conf/ida/StubbemannHS20
%A Stubbemann, Maximilian
%A Hanika, Tom
%A Stumme, Gerd
%B Advances in Intelligent Data Analysis {XVIII} - 18th International Symposium on Intelligent Data Analysis, {IDA} 2020, Konstanz, Germany, April 27-29, 2020, Proceedings
%D 2020
%E Berthold, Michael R.
%E Feelders, Ad
%E Krempl, Georg
%I Springer
%P 496--508
%R 10.1007/978-3-030-44584-3_39
%T Orometric Methods in Bounded Metric Data
%U https://doi.org/10.1007/978-3-030-44584-3\_39
%V 12080 - 1.Stumme, G.: On Ordinal Data Science and its role in Socially Acceptable ICTDesign. In: Hentschel, A., Hornung, G., and Jandt, S. (eds.) Mensch – Technik – Umwelt: Verantwortung für eine sozialverträgliche Zukunft, Festschrift für Alexander Roßnagel zum 70. Geburtstag. pp. 181–198. Nomos, Baden-Baden (2020).Comparing and ordering things is a basal ability of mankind for organizing its physical and social environment. While many hierarchical relationships can be derived from numerical measures like length or voltage, many others cannot appropriately be captured this way. We argue that the newly emerging field of data science up to now lacks engagement in developing analysis methods for such ordinal data. By the example of an already existing approach in this domain, Formal Concept Analysis, we will discuss its capabilities as a knowledge representation and argue – based on its philosophical foundations – why it is an important building block for socially acceptable IT design.
@inbook{stumme2020ordinal,
abstract = {Comparing and ordering things is a basal ability of mankind for organizing its physical and social environment. While many hierarchical relationships can be derived from numerical measures like length or voltage, many others cannot appropriately be captured this way. We argue that the newly emerging field of data science up to now lacks engagement in developing analysis methods for such ordinal data. By the example of an already existing approach in this domain, Formal Concept Analysis, we will discuss its capabilities as a knowledge representation and argue – based on its philosophical foundations – why it is an important building block for socially acceptable IT design.},
address = {Baden-Baden},
author = {Stumme, G.},
booktitle = {Mensch – Technik – Umwelt: Verantwortung für eine sozialverträgliche Zukunft, Festschrift für Alexander Roßnagel zum 70. Geburtstag},
editor = {Hentschel, A. and Hornung, G. and Jandt, S.},
keywords = {itegpub},
pages = {181-198},
publisher = {Nomos},
title = {On Ordinal Data Science and its role in Socially Acceptable ICTDesign},
year = 2020
}%0 Book Section
%1 stumme2020ordinal
%A Stumme, G.
%B Mensch – Technik – Umwelt: Verantwortung für eine sozialverträgliche Zukunft, Festschrift für Alexander Roßnagel zum 70. Geburtstag
%C Baden-Baden
%D 2020
%E Hentschel, A.
%E Hornung, G.
%E Jandt, S.
%I Nomos
%P 181-198
%T On Ordinal Data Science and its role in Socially Acceptable ICTDesign
%X Comparing and ordering things is a basal ability of mankind for organizing its physical and social environment. While many hierarchical relationships can be derived from numerical measures like length or voltage, many others cannot appropriately be captured this way. We argue that the newly emerging field of data science up to now lacks engagement in developing analysis methods for such ordinal data. By the example of an already existing approach in this domain, Formal Concept Analysis, we will discuss its capabilities as a knowledge representation and argue – based on its philosophical foundations – why it is an important building block for socially acceptable IT design.
%@ 978-3-8487-7014-4 - 1.Borchmann, D., Hanika, T., Obiedkov, S.: Probably approximately correct learning of Horn envelopes from queries. Discrete Applied Mathematics. 273, 30–42 (2020). https://doi.org/https://doi.org/10.1016/j.dam.2019.02.036.We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.
@article{BORCHMANN202030,
abstract = {We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.},
author = {Borchmann, Daniel and Hanika, Tom and Obiedkov, Sergei},
journal = {Discrete Applied Mathematics},
keywords = {itegpub},
note = {Advances in Formal Concept Analysis: Traces of CLA 2016},
pages = {30 - 42},
title = {Probably approximately correct learning of Horn envelopes from queries},
volume = 273,
year = 2020
}%0 Journal Article
%1 BORCHMANN202030
%A Borchmann, Daniel
%A Hanika, Tom
%A Obiedkov, Sergei
%D 2020
%J Discrete Applied Mathematics
%P 30 - 42
%R https://doi.org/10.1016/j.dam.2019.02.036
%T Probably approximately correct learning of Horn envelopes from queries
%U http://www.sciencedirect.com/science/article/pii/S0166218X19301295
%V 273
%X We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain. - 1.Schäfermeier, B., Stumme, G., Hanika, T.: Topic Space Trajectories: A case study on machine learning literature, http://arxiv.org/abs/2010.12294, (2020).The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present \emph{topic space trajectories}, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work.
@misc{schafermeier2020topic,
abstract = {The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present \emph{topic space trajectories}, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work.},
author = {Schäfermeier, Bastian and Stumme, Gerd and Hanika, Tom},
keywords = {itegpub},
note = {cite arxiv:2010.12294Comment: 36 pages, 8 figures},
title = {Topic Space Trajectories: A case study on machine learning literature},
year = 2020
}%0 Generic
%1 schafermeier2020topic
%A Schäfermeier, Bastian
%A Stumme, Gerd
%A Hanika, Tom
%D 2020
%T Topic Space Trajectories: A case study on machine learning literature
%U http://arxiv.org/abs/2010.12294
%X The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present \emph{topic space trajectories}, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50 years of machine learning research from 32 publication venues. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work.
2019
- 1.Dürrschnabel, D., Hanika, T., Stubbemann, M.: FCA2VEC: Embedding Techniques for Formal Concept Analysis, http://arxiv.org/abs/1911.11496, (2019).Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding latent semantic analysis recent approaches like word2vec or node2vec are well established tools in this realm. In the present paper we add to this line of research by introducing fca2vec, a family of embedding techniques for formal concept analysis (FCA). Our investigation contributes to two distinct lines of research. First, we enable the application of FCA notions to large data sets. In particular, we demonstrate how the cover relation of a concept lattice can be retrieved from a computational feasible embedding. Secondly, we show an enhancement for the classical node2vec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA community.
@misc{durrschnabel2019fca2vec,
abstract = {Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding latent semantic analysis recent approaches like word2vec or node2vec are well established tools in this realm. In the present paper we add to this line of research by introducing fca2vec, a family of embedding techniques for formal concept analysis (FCA). Our investigation contributes to two distinct lines of research. First, we enable the application of FCA notions to large data sets. In particular, we demonstrate how the cover relation of a concept lattice can be retrieved from a computational feasible embedding. Secondly, we show an enhancement for the classical node2vec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA community.},
author = {Dürrschnabel, Dominik and Hanika, Tom and Stubbemann, Maximilian},
keywords = {itegpub},
note = {cite arxiv:1911.11496Comment: 25 pages},
title = {FCA2VEC: Embedding Techniques for Formal Concept Analysis},
year = 2019
}%0 Generic
%1 durrschnabel2019fca2vec
%A Dürrschnabel, Dominik
%A Hanika, Tom
%A Stubbemann, Maximilian
%D 2019
%T FCA2VEC: Embedding Techniques for Formal Concept Analysis
%U http://arxiv.org/abs/1911.11496
%X Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding latent semantic analysis recent approaches like word2vec or node2vec are well established tools in this realm. In the present paper we add to this line of research by introducing fca2vec, a family of embedding techniques for formal concept analysis (FCA). Our investigation contributes to two distinct lines of research. First, we enable the application of FCA notions to large data sets. In particular, we demonstrate how the cover relation of a concept lattice can be retrieved from a computational feasible embedding. Secondly, we show an enhancement for the classical node2vec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA community. - 1.Felde, M., Hanika, T.: Formal Context Generation Using Dirichlet Distributions. In: Endres, D., Alam, M., and Sotropa, D. (eds.) ICCS. pp. 57–71. Springer (2019). https://doi.org/10.1007/978-3-030-23182-8_5.
@inproceedings{conf/iccs/FeldeH19,
author = {Felde, Maximilian and Hanika, Tom},
booktitle = {ICCS},
crossref = {conf/iccs/2019},
editor = {Endres, Dominik and Alam, Mehwish and Sotropa, Diana},
keywords = {itegpub},
pages = {57-71},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Formal Context Generation Using Dirichlet Distributions.},
volume = 11530,
year = 2019
}%0 Conference Paper
%1 conf/iccs/FeldeH19
%A Felde, Maximilian
%A Hanika, Tom
%B ICCS
%D 2019
%E Endres, Dominik
%E Alam, Mehwish
%E Sotropa, Diana
%I Springer
%P 57-71
%R 10.1007/978-3-030-23182-8_5
%T Formal Context Generation Using Dirichlet Distributions.
%U http://dblp.uni-trier.de/db/conf/iccs/iccs2019.html#FeldeH19
%V 11530
%@ 978-3-030-23182-8 - 1.Dürrschnabel, D., Hanika, T., Stumme, G.: Drawing Order Diagrams Through Two-Dimension Extension, http://arxiv.org/abs/1906.06208, (2019).Order diagrams are an important tool to visualize the complex structure of ordered sets. Favorable drawings of order diagrams, i.e., easily readable for humans, are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work we present the novel algorithm DimDraw to draw order diagrams. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of a corresponding graph.
@misc{durrschnabel2019drawing,
abstract = {Order diagrams are an important tool to visualize the complex structure of ordered sets. Favorable drawings of order diagrams, i.e., easily readable for humans, are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work we present the novel algorithm DimDraw to draw order diagrams. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of a corresponding graph.},
author = {Dürrschnabel, Dominik and Hanika, Tom and Stumme, Gerd},
keywords = {itegpub},
note = {cite arxiv:1906.06208Comment: 16 pages, 12 Figures},
title = {Drawing Order Diagrams Through Two-Dimension Extension},
year = 2019
}%0 Generic
%1 durrschnabel2019drawing
%A Dürrschnabel, Dominik
%A Hanika, Tom
%A Stumme, Gerd
%D 2019
%T Drawing Order Diagrams Through Two-Dimension Extension
%U http://arxiv.org/abs/1906.06208
%X Order diagrams are an important tool to visualize the complex structure of ordered sets. Favorable drawings of order diagrams, i.e., easily readable for humans, are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work we present the novel algorithm DimDraw to draw order diagrams. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of a corresponding graph. - 1.Felde, M., Stumme, G.: Interactive Collaborative Exploration using Incomplete Contexts, https://arxiv.org/abs/1908.08740, (2019).A common representation of information about relations of objects and attributes in knowledge domains are data-tables. The structure of such information can be analysed using Formal Concept Analysis (FCA). Attribute exploration is a knowledge acquisition method from FCA that reveals dependencies in a set of attributes with help of a domain expert. However, in general no single expert is capable (time- and knowledge-wise) of exploring knowledge domains alone. Therefore it is important to develop methods that allow multiple experts to explore domains together. To this end we build upon results on representation of incomplete knowledge [2, 8-10], adapt the corresponding version of attribute exploration to fit the setting of multiple experts and suggest formalizations for key components like expert knowledge, interaction and collaboration strategy. Furthermore we discuss ways of comparing collaboration strategies and suggest avenues for future research.
@misc{felde2019interactive,
abstract = {A common representation of information about relations of objects and attributes in knowledge domains are data-tables. The structure of such information can be analysed using Formal Concept Analysis (FCA). Attribute exploration is a knowledge acquisition method from FCA that reveals dependencies in a set of attributes with help of a domain expert. However, in general no single expert is capable (time- and knowledge-wise) of exploring knowledge domains alone. Therefore it is important to develop methods that allow multiple experts to explore domains together. To this end we build upon results on representation of incomplete knowledge [2, 8-10], adapt the corresponding version of attribute exploration to fit the setting of multiple experts and suggest formalizations for key components like expert knowledge, interaction and collaboration strategy. Furthermore we discuss ways of comparing collaboration strategies and suggest avenues for future research.},
author = {Felde, Maximilian and Stumme, Gerd},
keywords = {itegpub},
title = {Interactive Collaborative Exploration using Incomplete Contexts},
year = 2019
}%0 Generic
%1 felde2019interactive
%A Felde, Maximilian
%A Stumme, Gerd
%D 2019
%T Interactive Collaborative Exploration using Incomplete Contexts
%U https://arxiv.org/abs/1908.08740
%X A common representation of information about relations of objects and attributes in knowledge domains are data-tables. The structure of such information can be analysed using Formal Concept Analysis (FCA). Attribute exploration is a knowledge acquisition method from FCA that reveals dependencies in a set of attributes with help of a domain expert. However, in general no single expert is capable (time- and knowledge-wise) of exploring knowledge domains alone. Therefore it is important to develop methods that allow multiple experts to explore domains together. To this end we build upon results on representation of incomplete knowledge [2, 8-10], adapt the corresponding version of attribute exploration to fit the setting of multiple experts and suggest formalizations for key components like expert knowledge, interaction and collaboration strategy. Furthermore we discuss ways of comparing collaboration strategies and suggest avenues for future research. - 1.Hanika, T., Kibanov, M., Kropf, J., Laser, S.: Ich denke, es ist wichtig zu verstehen, warum die Netzwerkanalyse jetzt popul{ä}r und besonders interessant f{ü}r die Forschung geworden ist. In: Kropf, J. and Laser, S. (eds.) Digitale Bewertungspraktiken. pp. 165–188. Springer (2019).
@incollection{hanika2019denke,
author = {Hanika, Tom and Kibanov, Mark and Kropf, Jonathan and Laser, Stefan},
booktitle = {Digitale Bewertungspraktiken},
editor = {Kropf, Jonathan and Laser, Stefan},
keywords = {bewertungspraktiken},
pages = {165--188},
publisher = {Springer},
title = {Ich denke, es ist wichtig zu verstehen, warum die Netzwerkanalyse jetzt popul{ä}r und besonders interessant f{ü}r die Forschung geworden ist.},
year = 2019
}%0 Book Section
%1 hanika2019denke
%A Hanika, Tom
%A Kibanov, Mark
%A Kropf, Jonathan
%A Laser, Stefan
%B Digitale Bewertungspraktiken
%D 2019
%E Kropf, Jonathan
%E Laser, Stefan
%I Springer
%P 165--188
%T Ich denke, es ist wichtig zu verstehen, warum die Netzwerkanalyse jetzt popul{ä}r und besonders interessant f{ü}r die Forschung geworden ist. - 1.Hanika, T.: Discovering Knowledge in Bipartite Graphs with Formal Concept Analysis., (2019). https://doi.org/10.17170/kobra-20190213189.
@phdthesis{phd/dnb/Hanika19,
author = {Hanika, Tom},
keywords = {itegpub},
school = {University of Kassel, Germany},
title = {Discovering Knowledge in Bipartite Graphs with Formal Concept Analysis.},
year = 2019
}%0 Thesis
%1 phd/dnb/Hanika19
%A Hanika, Tom
%D 2019
%R 10.17170/kobra-20190213189
%T Discovering Knowledge in Bipartite Graphs with Formal Concept Analysis. - 1.Hanika, T., Hirth, J.: Conexp-Clj - A Research Tool for FCA. In: Cristea, D., Ber, F.L., Missaoui, R., Kwuida, L., and Sertkaya, B. (eds.) ICFCA (Supplements). pp. 70–75. CEUR-WS.org (2019).
@inproceedings{conf/icfca/HanikaH19,
author = {Hanika, Tom and Hirth, Johannes},
booktitle = {ICFCA (Supplements)},
crossref = {conf/icfca/2019suppl},
editor = {Cristea, Diana and Ber, Florence Le and Missaoui, Rokia and Kwuida, Léonard and Sertkaya, Baris},
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}%0 Conference Paper
%1 conf/icfca/HanikaH19
%A Hanika, Tom
%A Hirth, Johannes
%B ICFCA (Supplements)
%D 2019
%E Cristea, Diana
%E Ber, Florence Le
%E Missaoui, Rokia
%E Kwuida, Léonard
%E Sertkaya, Baris
%I CEUR-WS.org
%P 70-75
%T Conexp-Clj - A Research Tool for FCA.
%U http://dblp.uni-trier.de/db/conf/icfca/icfca2019suppl.html#HanikaH19
%V 2378 - 1.Hanika, T., Herde, M., Kuhn, J., Leimeister, J.M., Lukowicz, P., Oeste-Reiß, S., Schmidt, A., Sick, B., Stumme, G., Tomforde, S., Zweig, K.A.: Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields. CoRR. abs/1905.07264, (2019).
@article{journals/corr/abs-1905-07264,
author = {Hanika, Tom and Herde, Marek and Kuhn, Jochen and Leimeister, Jan Marco and Lukowicz, Paul and Oeste-Reiß, Sarah and Schmidt, Albrecht and Sick, Bernhard and Stumme, Gerd and Tomforde, Sven and Zweig, Katharina Anna},
journal = {CoRR},
keywords = {itegpub},
title = {Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields.},
volume = {abs/1905.07264},
year = 2019
}%0 Journal Article
%1 journals/corr/abs-1905-07264
%A Hanika, Tom
%A Herde, Marek
%A Kuhn, Jochen
%A Leimeister, Jan Marco
%A Lukowicz, Paul
%A Oeste-Reiß, Sarah
%A Schmidt, Albrecht
%A Sick, Bernhard
%A Stumme, Gerd
%A Tomforde, Sven
%A Zweig, Katharina Anna
%D 2019
%J CoRR
%T Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields.
%U http://dblp.uni-trier.de/db/journals/corr/corr1905.html#abs-1905-07264
%V abs/1905.07264 - 1.Schäfermeier, B., Hanika, T., Stumme, G.: Distances for WiFi Based Topological Indoor Mapping. In: 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous), November 12--14, 2019, Houston, TX, USA (2019). https://doi.org/10.1145/3360774.3360780.For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator. In this work we compare various measures of distance between such likelihoods in combination with different methods for estimation and representation. In particular, we show that among the considered distance measures the Earth Mover's Distance seems the most beneficial for the localization task. Combined with kernel density estimation we were able to retain the topological structure of rooms in a real-world office scenario.
@inproceedings{schafermeier2019distances,
abstract = {For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator. In this work we compare various measures of distance between such likelihoods in combination with different methods for estimation and representation. In particular, we show that among the considered distance measures the Earth Mover's Distance seems the most beneficial for the localization task. Combined with kernel density estimation we were able to retain the topological structure of rooms in a real-world office scenario.},
author = {Schäfermeier, Bastian and Hanika, Tom and Stumme, Gerd},
booktitle = {16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous), November 12--14, 2019, Houston, TX, USA},
keywords = {itegpub},
title = {Distances for WiFi Based Topological Indoor Mapping},
year = 2019
}%0 Conference Paper
%1 schafermeier2019distances
%A Schäfermeier, Bastian
%A Hanika, Tom
%A Stumme, Gerd
%B 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous), November 12--14, 2019, Houston, TX, USA
%D 2019
%R 10.1145/3360774.3360780
%T Distances for WiFi Based Topological Indoor Mapping
%X For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator. In this work we compare various measures of distance between such likelihoods in combination with different methods for estimation and representation. In particular, we show that among the considered distance measures the Earth Mover's Distance seems the most beneficial for the localization task. Combined with kernel density estimation we were able to retain the topological structure of rooms in a real-world office scenario.
%@ 978-1-4503-7283-1/19/11 - 1.Dürrschnabel, D., Hanika, T., Stumme, G.: DimDraw - A Novel Tool for Drawing Concept Lattices. In: Cristea, D., Ber, F.L., Missaoui, R., Kwuida, L., and Sertkaya, B. (eds.) ICFCA (Supplements). pp. 60–64. CEUR-WS.org (2019).
@inproceedings{conf/icfca/DurrschnabelHS19,
author = {Dürrschnabel, Dominik and Hanika, Tom and Stumme, Gerd},
booktitle = {ICFCA (Supplements)},
crossref = {conf/icfca/2019suppl},
editor = {Cristea, Diana and Ber, Florence Le and Missaoui, Rokia and Kwuida, Léonard and Sertkaya, Baris},
keywords = {itegpub},
pages = {60-64},
publisher = {CEUR-WS.org},
series = {CEUR Workshop Proceedings},
title = {DimDraw - A Novel Tool for Drawing Concept Lattices.},
volume = 2378,
year = 2019
}%0 Conference Paper
%1 conf/icfca/DurrschnabelHS19
%A Dürrschnabel, Dominik
%A Hanika, Tom
%A Stumme, Gerd
%B ICFCA (Supplements)
%D 2019
%E Cristea, Diana
%E Ber, Florence Le
%E Missaoui, Rokia
%E Kwuida, Léonard
%E Sertkaya, Baris
%I CEUR-WS.org
%P 60-64
%T DimDraw - A Novel Tool for Drawing Concept Lattices.
%U http://dblp.uni-trier.de/db/conf/icfca/icfca2019suppl.html#DurrschnabelHS19
%V 2378 - 1.Hanika, T., Marx, M., Stumme, G.: Discovering Implicational Knowledge in Wikidata. In: Cristea, D., Ber, F.L., and Sertkaya, B. (eds.) Formal Concept Analysis - 15th International Conference, {ICFCA} 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings. pp. 315–323. Springer (2019). https://doi.org/10.1007/978-3-030-21462-3_21.
@inproceedings{DBLP:conf/icfca/Hanika0S19,
author = {Hanika, Tom and Marx, Maximilian and Stumme, Gerd},
booktitle = {Formal Concept Analysis - 15th International Conference, {ICFCA} 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings},
editor = {Cristea, Diana and Ber, Florence Le and Sertkaya, Baris},
keywords = {kdepub},
pages = {315--323},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Discovering Implicational Knowledge in Wikidata},
volume = 11511,
year = 2019
}%0 Conference Paper
%1 DBLP:conf/icfca/Hanika0S19
%A Hanika, Tom
%A Marx, Maximilian
%A Stumme, Gerd
%B Formal Concept Analysis - 15th International Conference, {ICFCA} 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings
%D 2019
%E Cristea, Diana
%E Ber, Florence Le
%E Sertkaya, Baris
%I Springer
%P 315--323
%R 10.1007/978-3-030-21462-3_21
%T Discovering Implicational Knowledge in Wikidata
%U https://doi.org/10.1007/978-3-030-21462-3_21
%V 11511 - 1.Stubbemann, M., Hanika, T., Stumme, G.: Orometric Methods in Bounded Metric Data. CoRR. abs/1907.09239, (2019).
@article{journals/corr/abs-1907-09239,
author = {Stubbemann, Maximilian and Hanika, Tom and Stumme, Gerd},
journal = {CoRR},
keywords = {preprint},
note = {Accept for IDA 2020},
title = {Orometric Methods in Bounded Metric Data.},
volume = {abs/1907.09239},
year = 2019
}%0 Journal Article
%1 journals/corr/abs-1907-09239
%A Stubbemann, Maximilian
%A Hanika, Tom
%A Stumme, Gerd
%D 2019
%J CoRR
%T Orometric Methods in Bounded Metric Data.
%U http://dblp.uni-trier.de/db/journals/corr/corr1907.html#abs-1907-09239
%V abs/1907.09239 - 1.Schaefermeier, B., Hanika, T., Stumme, G.: Distances for wifi based topological indoor mapping. In: Proceedings of the 16th {EAI} International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. {ACM} (2019). https://doi.org/10.1145/3360774.3360780.
@inproceedings{Schaefermeier_2019,
author = {Schaefermeier, Bastian and Hanika, Tom and Stumme, Gerd},
booktitle = {Proceedings of the 16th {EAI} International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},
keywords = {itegpub},
month = 11,
publisher = {{ACM}},
title = {Distances for wifi based topological indoor mapping},
year = 2019
}%0 Conference Paper
%1 Schaefermeier_2019
%A Schaefermeier, Bastian
%A Hanika, Tom
%A Stumme, Gerd
%B Proceedings of the 16th {EAI} International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
%D 2019
%I {ACM}
%R 10.1145/3360774.3360780
%T Distances for wifi based topological indoor mapping
%U https://doi.org/10.1145%2F3360774.3360780 - 1.Kibanov, M., Heiberger, R.H., R{ö}dder, S., Atzmueller, M., Stumme, G.: Social studies of scholarly life with sensor-based ethnographic observations. Scientometrics. (2019). https://doi.org/10.1007/s11192-019-03097-w.Social network analysis is playing an increasingly important role in sociological studies. At the same time, new technologies such as wearable sensors make it possible to collect new types of social network data. We employed RFID tags to capture face-to-face interactions of participants of two consecutive Ph.D. retreats of a graduate school on climate research. We use this data in order to explore how it may support ethnographic observations and to gain further insights on scholarly interactions. The unique feature of the data is the opportunity to distinguish short and long conversations, which often have a different nature from a sociological point of view. Furthermore, an advantage of this data is the availability of socio-demographic, research-related, and situational attributes of participants. We show that, even though an interaction partner is often found rather randomly during coffee breaks of retreats, a strong homophily between participants from the same institutions or research areas exists. We identify cores of the networks and participants who play ambassador roles between communities, e.g., persons who visit the retreat for the second time are more likely to be ambassadors. Overall, we show the usefulness and potential of RFID tags for scientometric studies.
@article{kibanov2019social,
abstract = {Social network analysis is playing an increasingly important role in sociological studies. At the same time, new technologies such as wearable sensors make it possible to collect new types of social network data. We employed RFID tags to capture face-to-face interactions of participants of two consecutive Ph.D. retreats of a graduate school on climate research. We use this data in order to explore how it may support ethnographic observations and to gain further insights on scholarly interactions. The unique feature of the data is the opportunity to distinguish short and long conversations, which often have a different nature from a sociological point of view. Furthermore, an advantage of this data is the availability of socio-demographic, research-related, and situational attributes of participants. We show that, even though an interaction partner is often found rather randomly during coffee breaks of retreats, a strong homophily between participants from the same institutions or research areas exists. We identify cores of the networks and participants who play ambassador roles between communities, e.g., persons who visit the retreat for the second time are more likely to be ambassadors. Overall, we show the usefulness and potential of RFID tags for scientometric studies.},
author = {Kibanov, Mark and Heiberger, Raphael H. and R{ö}dder, Simone and Atzmueller, Martin and Stumme, Gerd},
journal = {Scientometrics},
keywords = {homophily},
month = {05},
title = {Social studies of scholarly life with sensor-based ethnographic observations},
year = 2019
}%0 Journal Article
%1 kibanov2019social
%A Kibanov, Mark
%A Heiberger, Raphael H.
%A R{ö}dder, Simone
%A Atzmueller, Martin
%A Stumme, Gerd
%D 2019
%J Scientometrics
%R 10.1007/s11192-019-03097-w
%T Social studies of scholarly life with sensor-based ethnographic observations
%U https://doi.org/10.1007/s11192-019-03097-w
%X Social network analysis is playing an increasingly important role in sociological studies. At the same time, new technologies such as wearable sensors make it possible to collect new types of social network data. We employed RFID tags to capture face-to-face interactions of participants of two consecutive Ph.D. retreats of a graduate school on climate research. We use this data in order to explore how it may support ethnographic observations and to gain further insights on scholarly interactions. The unique feature of the data is the opportunity to distinguish short and long conversations, which often have a different nature from a sociological point of view. Furthermore, an advantage of this data is the availability of socio-demographic, research-related, and situational attributes of participants. We show that, even though an interaction partner is often found rather randomly during coffee breaks of retreats, a strong homophily between participants from the same institutions or research areas exists. We identify cores of the networks and participants who play ambassador roles between communities, e.g., persons who visit the retreat for the second time are more likely to be ambassadors. Overall, we show the usefulness and potential of RFID tags for scientometric studies. - 1.Hanika, T., Koyda, M., Stumme, G.: Relevant Attributes in Formal Contexts. In: Endres, D., Alam, M., and Sotropa, D. (eds.) ICCS. pp. 102–116. Springer (2019). https://doi.org/10.1007/978-3-030-23182-8_8.
@inproceedings{conf/iccs/HanikaKS19,
author = {Hanika, Tom and Koyda, Maren and Stumme, Gerd},
booktitle = {ICCS},
crossref = {conf/iccs/2019},
editor = {Endres, Dominik and Alam, Mehwish and Sotropa, Diana},
keywords = {itegpub},
pages = {102-116},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Relevant Attributes in Formal Contexts.},
volume = 11530,
year = 2019
}%0 Conference Paper
%1 conf/iccs/HanikaKS19
%A Hanika, Tom
%A Koyda, Maren
%A Stumme, Gerd
%B ICCS
%D 2019
%E Endres, Dominik
%E Alam, Mehwish
%E Sotropa, Diana
%I Springer
%P 102-116
%R 10.1007/978-3-030-23182-8_8
%T Relevant Attributes in Formal Contexts.
%U http://dblp.uni-trier.de/db/conf/iccs/iccs2019.html#HanikaKS19
%V 11530
%@ 978-3-030-23182-8
2018
- 1.Kibanov, M., Becker, M., Müller, J., Atzmueller, M., Hotho, A., Stumme, G.: {Adaptive kNN Using Expected Accuracy for Classification of Geo-Spatial Data}. In: Proc. 33rd ACM Symposium On Applied Computing. ACM Press, New York, NY, USA (2018).
@inproceedings{KBMAHS:18,
address = {New York, NY, USA},
author = {Kibanov, Mark and Becker, Martin and Müller, Jürgen and Atzmueller, Martin and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proc. 33rd ACM Symposium On Applied Computing},
keywords = {classification},
publisher = {ACM Press},
title = {{Adaptive kNN Using Expected Accuracy for Classification of Geo-Spatial Data}},
year = 2018
}%0 Conference Paper
%1 KBMAHS:18
%A Kibanov, Mark
%A Becker, Martin
%A Müller, Jürgen
%A Atzmueller, Martin
%A Hotho, Andreas
%A Stumme, Gerd
%B Proc. 33rd ACM Symposium On Applied Computing
%C New York, NY, USA
%D 2018
%I ACM Press
%T {Adaptive kNN Using Expected Accuracy for Classification of Geo-Spatial Data} - 1.Thiele, L., Atzmueller, M., Stumme, G., Kauffeld, S.: {Frequent and/or Durable? The Predictive Impact of Initial Face-to-Face Contacts on the Formation and Evolution of Developmental Peer Network Relationships}. Psychology. (2018).
@article{TASK:18,
author = {Thiele, Lisa and Atzmueller, Martin and Stumme, Gerd and Kauffeld, Simone},
journal = {Psychology},
keywords = {face-to-face},
month = {(In Press)},
title = {{Frequent and/or Durable? The Predictive Impact of Initial Face-to-Face Contacts on the Formation and Evolution of Developmental Peer Network Relationships}},
year = 2018
}%0 Journal Article
%1 TASK:18
%A Thiele, Lisa
%A Atzmueller, Martin
%A Stumme, Gerd
%A Kauffeld, Simone
%D 2018
%J Psychology
%T {Frequent and/or Durable? The Predictive Impact of Initial Face-to-Face Contacts on the Formation and Evolution of Developmental Peer Network Relationships} - 1.Hanika, T., Schneider, F.M., Stumme, G.: Intrinsic dimension of concept lattices. CoRR. abs/1801.07985, (2018).Geometric analysis is a very capable theory to understand the influence of the high dimensionality of the input data in machine learning (ML) and knowledge discovery (KD). With our approach we can assess how far the application of a specific KD/ML-algorithm to a concrete data set is prone to the curse of dimensionality. To this end we extend V.~Pestov's axiomatic approach to the instrinsic dimension of data sets, based on the seminal work by M.~Gromov on concentration phenomena, and provide an adaptable and computationally feasible model for studying observable geometric invariants associated to features that are natural to both the data and the learning procedure. In detail, we investigate data represented by formal contexts and give first theoretical as well as experimental insights into the intrinsic dimension of a concept lattice. Because of the correspondence between formal concepts and maximal cliques in graphs, applications to social network analysis are at hand.
@article{hanika2018intrinsic,
abstract = {Geometric analysis is a very capable theory to understand the influence of the high dimensionality of the input data in machine learning (ML) and knowledge discovery (KD). With our approach we can assess how far the application of a specific KD/ML-algorithm to a concrete data set is prone to the curse of dimensionality. To this end we extend V.~Pestov's axiomatic approach to the instrinsic dimension of data sets, based on the seminal work by M.~Gromov on concentration phenomena, and provide an adaptable and computationally feasible model for studying observable geometric invariants associated to features that are natural to both the data and the learning procedure. In detail, we investigate data represented by formal contexts and give first theoretical as well as experimental insights into the intrinsic dimension of a concept lattice. Because of the correspondence between formal concepts and maximal cliques in graphs, applications to social network analysis are at hand.},
author = {Hanika, Tom and Schneider, Friedrich Martin and Stumme, Gerd},
journal = {CoRR},
keywords = {dimension},
note = {cite arxiv:1801.07985Comment: 13 pages, 3 figures},
title = {Intrinsic dimension of concept lattices},
volume = {abs/1801.07985},
year = 2018
}%0 Journal Article
%1 hanika2018intrinsic
%A Hanika, Tom
%A Schneider, Friedrich Martin
%A Stumme, Gerd
%D 2018
%J CoRR
%T Intrinsic dimension of concept lattices
%U http://arxiv.org/abs/1801.07985
%V abs/1801.07985
%X Geometric analysis is a very capable theory to understand the influence of the high dimensionality of the input data in machine learning (ML) and knowledge discovery (KD). With our approach we can assess how far the application of a specific KD/ML-algorithm to a concrete data set is prone to the curse of dimensionality. To this end we extend V.~Pestov's axiomatic approach to the instrinsic dimension of data sets, based on the seminal work by M.~Gromov on concentration phenomena, and provide an adaptable and computationally feasible model for studying observable geometric invariants associated to features that are natural to both the data and the learning procedure. In detail, we investigate data represented by formal contexts and give first theoretical as well as experimental insights into the intrinsic dimension of a concept lattice. Because of the correspondence between formal concepts and maximal cliques in graphs, applications to social network analysis are at hand. - 1.Hanika, T., Schneider, F.M., Stumme, G.: Intrinsic Dimension of Geometric Data Sets, http://arxiv.org/abs/1801.07985, (2018).The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our mathematical model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments.
@misc{hanika2018intrinsic,
abstract = {The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our mathematical model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments.},
author = {Hanika, Tom and Schneider, Friedrich Martin and Stumme, Gerd},
keywords = {itegpub},
note = {cite arxiv:1801.07985Comment: v2: completely rewritten 28 pages, 3 figures, 2 tables},
title = {Intrinsic Dimension of Geometric Data Sets},
year = 2018
}%0 Generic
%1 hanika2018intrinsic
%A Hanika, Tom
%A Schneider, Friedrich Martin
%A Stumme, Gerd
%D 2018
%T Intrinsic Dimension of Geometric Data Sets
%U http://arxiv.org/abs/1801.07985
%X The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our mathematical model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML/KD-algorithms, as illustrated by various experiments. - 1.Schäfermeier, B., Hanika, T., Stumme, G.: Distances for WiFi Based Topological Indoor Mapping, http://arxiv.org/abs/1809.07405, (2018).For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator. In this work we compare various measures of distance between such likelihoods in combination with different methods for estimation and representation. In particular, we show that among the considered distance measures the Earth Mover's Distance seems the most beneficial for the localization task. Combined with kernel density estimation we were able to retain the topological structure of rooms in a real-world office scenario.
@misc{schafermeier2018distances,
abstract = {For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator. In this work we compare various measures of distance between such likelihoods in combination with different methods for estimation and representation. In particular, we show that among the considered distance measures the Earth Mover's Distance seems the most beneficial for the localization task. Combined with kernel density estimation we were able to retain the topological structure of rooms in a real-world office scenario.},
author = {Schäfermeier, Bastian and Hanika, Tom and Stumme, Gerd},
keywords = {itegpub},
note = {cite arxiv:1809.07405Comment: 10 pages, 6 figures},
title = {Distances for WiFi Based Topological Indoor Mapping},
year = 2018
}%0 Generic
%1 schafermeier2018distances
%A Schäfermeier, Bastian
%A Hanika, Tom
%A Stumme, Gerd
%D 2018
%T Distances for WiFi Based Topological Indoor Mapping
%U http://arxiv.org/abs/1809.07405
%X For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator. In this work we compare various measures of distance between such likelihoods in combination with different methods for estimation and representation. In particular, we show that among the considered distance measures the Earth Mover's Distance seems the most beneficial for the localization task. Combined with kernel density estimation we were able to retain the topological structure of rooms in a real-world office scenario. - 1.Doerfel, S., Hanika, T., Stumme, G.: Clones in Social Networks. CoRR. abs/1802.07849, (2018).It is well known that any bipartite (social) network can be regarded as a formal context $(G,M,I)$. Therefore, such networks give raise to formal concept lattices which can be investigated utilizing the toolset of Formal Concept Analysis (FCA). In particular, the notion of clones in closure systems on $M$, i.e., pairwise interchangeable attributes that leave the closure system unchanged, suggests itself naturally as a candidate to be analyzed in the realm of FCA based social network analysis. In this study, we investigate the notion of clones in social networks. After building up some theoretical background for the clone relation in formal contexts we try to find clones in real word data sets. To this end, we provide an experimental evaluation on nine mostly well known social networks and provide some first insights on the impact of clones. We conclude our work by nourishing the understanding of clones by generalizing those to permutations of higher order.
@article{doerfel2018clones,
abstract = {It is well known that any bipartite (social) network can be regarded as a formal context $(G,M,I)$. Therefore, such networks give raise to formal concept lattices which can be investigated utilizing the toolset of Formal Concept Analysis (FCA). In particular, the notion of clones in closure systems on $M$, i.e., pairwise interchangeable attributes that leave the closure system unchanged, suggests itself naturally as a candidate to be analyzed in the realm of FCA based social network analysis. In this study, we investigate the notion of clones in social networks. After building up some theoretical background for the clone relation in formal contexts we try to find clones in real word data sets. To this end, we provide an experimental evaluation on nine mostly well known social networks and provide some first insights on the impact of clones. We conclude our work by nourishing the understanding of clones by generalizing those to permutations of higher order.},
author = {Doerfel, Stephan and Hanika, Tom and Stumme, Gerd},
journal = {CoRR},
keywords = {networks},
note = {cite arxiv:1802.07849Comment: 12 pages, 2 figures, 2 tables},
title = {Clones in Social Networks},
volume = {abs/1802.07849},
year = 2018
}%0 Journal Article
%1 doerfel2018clones
%A Doerfel, Stephan
%A Hanika, Tom
%A Stumme, Gerd
%D 2018
%J CoRR
%T Clones in Social Networks
%U http://arxiv.org/abs/1802.07849
%V abs/1802.07849
%X It is well known that any bipartite (social) network can be regarded as a formal context $(G,M,I)$. Therefore, such networks give raise to formal concept lattices which can be investigated utilizing the toolset of Formal Concept Analysis (FCA). In particular, the notion of clones in closure systems on $M$, i.e., pairwise interchangeable attributes that leave the closure system unchanged, suggests itself naturally as a candidate to be analyzed in the realm of FCA based social network analysis. In this study, we investigate the notion of clones in social networks. After building up some theoretical background for the clone relation in formal contexts we try to find clones in real word data sets. To this end, we provide an experimental evaluation on nine mostly well known social networks and provide some first insights on the impact of clones. We conclude our work by nourishing the understanding of clones by generalizing those to permutations of higher order. - 1.Hanika, T., Koyda, M., Stumme, G.: Relevant Attributes in Formal Contexts. CoRR. abs/1812.08868, (2018).
@article{journals/corr/abs-1812-08868,
author = {Hanika, Tom and Koyda, Maren and Stumme, Gerd},
journal = {CoRR},
keywords = {relevance},
note = {Accepted for ICCS'19},
title = {Relevant Attributes in Formal Contexts.},
volume = {abs/1812.08868},
year = 2018
}%0 Journal Article
%1 journals/corr/abs-1812-08868
%A Hanika, Tom
%A Koyda, Maren
%A Stumme, Gerd
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%T Relevant Attributes in Formal Contexts.
%U http://dblp.uni-trier.de/db/journals/corr/corr1812.html#abs-1812-08868
%V abs/1812.08868 - 1.Borchmann, D., Hanika, T., Obiedkov, S.: Probably approximately correct learning of Horn envelopes from queries. CoRR. abs/1807.06149, (2018).We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.
@article{journals/corr/abs-1807-06149,
abstract = {We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.},
author = {Borchmann, Daniel and Hanika, Tom and Obiedkov, Sergei},
journal = {CoRR},
keywords = {preprint},
note = {cite arxiv:1807.06149Comment: 21 pages, 1 figure},
title = {Probably approximately correct learning of Horn envelopes from queries.},
volume = {abs/1807.06149},
year = 2018
}%0 Journal Article
%1 journals/corr/abs-1807-06149
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%J CoRR
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%V abs/1807.06149
%X We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain. - 1.Axenovich, M., Dürrschnabel, D.: Subsets of vertices of the same size and the same maximum distance. 5, (2018).
@article{axenovich2018subsets,
author = {Axenovich, Maria and Dürrschnabel, Dominik},
keywords = 2018,
number = 2,
title = {Subsets of vertices of the same size and the same maximum distance},
volume = 5,
year = 2018
}%0 Journal Article
%1 axenovich2018subsets
%A Axenovich, Maria
%A Dürrschnabel, Dominik
%D 2018
%N 2
%T Subsets of vertices of the same size and the same maximum distance
%U https://digitalcommons.georgiasouthern.edu/tag/vol5/iss2/7/
%V 5 - 1.Hanika, T., Schneider, F.M., Stumme, G.: Intrinsic dimension and its application to association rules. CoRR. abs/1805.05714, (2018).The curse of dimensionality in the realm of association rules is twofold. Firstly, we have the well known exponential increase in computational complexity with increasing item set size. Secondly, there is a \emph{related curse} concerned with the distribution of (spare) data itself in high dimension. The former problem is often coped with by projection, i.e., feature selection, whereas the best known strategy for the latter is avoidance. This work summarizes the first attempt to provide a computationally feasible method for measuring the extent of dimension curse present in a data set with respect to a particular class machine of learning procedures. This recent development enables the application of various other methods from geometric analysis to be investigated and applied in machine learning procedures in the presence of high dimension.
@article{hanika2018intrinsic,
abstract = {The curse of dimensionality in the realm of association rules is twofold. Firstly, we have the well known exponential increase in computational complexity with increasing item set size. Secondly, there is a \emph{related curse} concerned with the distribution of (spare) data itself in high dimension. The former problem is often coped with by projection, i.e., feature selection, whereas the best known strategy for the latter is avoidance. This work summarizes the first attempt to provide a computationally feasible method for measuring the extent of dimension curse present in a data set with respect to a particular class machine of learning procedures. This recent development enables the application of various other methods from geometric analysis to be investigated and applied in machine learning procedures in the presence of high dimension.},
author = {Hanika, Tom and Schneider, Friedrich Martin and Stumme, Gerd},
journal = {CoRR},
keywords = {dimension},
note = {cite arxiv:1805.05714Comment: 4 pages, 1 figure},
title = {Intrinsic dimension and its application to association rules},
volume = {abs/1805.05714},
year = 2018
}%0 Journal Article
%1 hanika2018intrinsic
%A Hanika, Tom
%A Schneider, Friedrich Martin
%A Stumme, Gerd
%D 2018
%J CoRR
%T Intrinsic dimension and its application to association rules
%U http://arxiv.org/abs/1805.05714
%V abs/1805.05714
%X The curse of dimensionality in the realm of association rules is twofold. Firstly, we have the well known exponential increase in computational complexity with increasing item set size. Secondly, there is a \emph{related curse} concerned with the distribution of (spare) data itself in high dimension. The former problem is often coped with by projection, i.e., feature selection, whereas the best known strategy for the latter is avoidance. This work summarizes the first attempt to provide a computationally feasible method for measuring the extent of dimension curse present in a data set with respect to a particular class machine of learning procedures. This recent development enables the application of various other methods from geometric analysis to be investigated and applied in machine learning procedures in the presence of high dimension. - 1.Navarro Bullock, B., Hotho, A., Stumme, G.: Accessing Information with Tags: Search and Ranking. In: Brusilovsky, P. and He, D. (eds.) Social Information Access: Systems and Technologies. pp. 310–343. Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-90092-6_9.With the growth of the Social Web, a variety of new web-based services arose and changed the way users interact with the internet and consume information. One central phenomenon was and is tagging which allows to manage, organize and access information in social systems. Tagging helps to manage all kinds of resources, making their access much easier. The first type of social tagging systems were social bookmarking systems, i.e., platforms for storing and sharing bookmarks on the web rather than just in the browser. Meanwhile, (hash-)tagging is central in many other Social Media systems such as social networking sites and micro-blogging platforms. To allow for efficient information access, special algorithms have been developed to guide the user, to search for information and to rank the content based on tagging information contributed by the users.
@inbook{NavarroBullock2018,
abstract = {With the growth of the Social Web, a variety of new web-based services arose and changed the way users interact with the internet and consume information. One central phenomenon was and is tagging which allows to manage, organize and access information in social systems. Tagging helps to manage all kinds of resources, making their access much easier. The first type of social tagging systems were social bookmarking systems, i.e., platforms for storing and sharing bookmarks on the web rather than just in the browser. Meanwhile, (hash-)tagging is central in many other Social Media systems such as social networking sites and micro-blogging platforms. To allow for efficient information access, special algorithms have been developed to guide the user, to search for information and to rank the content based on tagging information contributed by the users.},
address = {Cham},
author = {Navarro Bullock, Beate and Hotho, Andreas and Stumme, Gerd},
booktitle = {Social Information Access: Systems and Technologies},
editor = {Brusilovsky, Peter and He, Daqing},
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%X With the growth of the Social Web, a variety of new web-based services arose and changed the way users interact with the internet and consume information. One central phenomenon was and is tagging which allows to manage, organize and access information in social systems. Tagging helps to manage all kinds of resources, making their access much easier. The first type of social tagging systems were social bookmarking systems, i.e., platforms for storing and sharing bookmarks on the web rather than just in the browser. Meanwhile, (hash-)tagging is central in many other Social Media systems such as social networking sites and micro-blogging platforms. To allow for efficient information access, special algorithms have been developed to guide the user, to search for information and to rank the content based on tagging information contributed by the users.
%@ 978-3-319-90092-6 - 1.Felde, M., Hanika, T.: Formal Context Generation using Dirichlet Distributions. CoRR. abs/1809.11160, (2018).
@article{journals/corr/abs-1809-11160,
author = {Felde, Maximilian and Hanika, Tom},
journal = {CoRR},
keywords = {kde},
note = {Accepted for ICCS'19},
title = {Formal Context Generation using Dirichlet Distributions.},
volume = {abs/1809.11160},
year = 2018
}%0 Journal Article
%1 journals/corr/abs-1809-11160
%A Felde, Maximilian
%A Hanika, Tom
%D 2018
%J CoRR
%T Formal Context Generation using Dirichlet Distributions.
%U http://dblp.uni-trier.de/db/journals/corr/corr1809.html#abs-1809-11160
%V abs/1809.11160 - 1.Doerfel, S., Hanika, T., Stumme, G.: Clones in Graphs. In: Ceci, M., Japkowicz, N., Liu, J., Papadopoulos, G.A., and Ras, Z.W. (eds.) ISMIS. pp. 56–66. Springer (2018). https://doi.org/10.1007/978-3-030-01851-1_6.
@inproceedings{conf/ismis/DoerfelHS18,
author = {Doerfel, Stephan and Hanika, Tom and Stumme, Gerd},
booktitle = {ISMIS},
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editor = {Ceci, Michelangelo and Japkowicz, Nathalie and Liu, Jiming and Papadopoulos, George A. and Ras, Zbigniew W.},
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%@ 978-3-030-01851-1 - 1.Thiele, L., Atzmueller, M., Stumme, G., Kauffeld, S.: Frequent and/or Durable? The Predictive Impact of Initial Face-to-Face Contacts on the Formation and Evolution of Students’ Developmental Peer Network Relationships. Psychology. 09, 633–654 (2018). https://doi.org/10.4236/psych.2018.94040.
@article{thiele2018frequent,
author = {Thiele, Lisa and Atzmueller, Martin and Stumme, Gerd and Kauffeld, Simone},
journal = {Psychology},
keywords = {itegpub},
number = {04},
pages = {633--654},
publisher = {Scientific Research Publishing, Inc,},
title = {Frequent and/or Durable? The Predictive Impact of Initial Face-to-Face Contacts on the Formation and Evolution of Students' Developmental Peer Network Relationships},
volume = {09},
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}%0 Journal Article
%1 thiele2018frequent
%A Thiele, Lisa
%A Atzmueller, Martin
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%D 2018
%I Scientific Research Publishing, Inc,
%J Psychology
%N 04
%P 633--654
%R 10.4236/psych.2018.94040
%T Frequent and/or Durable? The Predictive Impact of Initial Face-to-Face Contacts on the Formation and Evolution of Students' Developmental Peer Network Relationships
%U https://doi.org/10.4236%2Fpsych.2018.94040
%V 09 - 1.Demel, A., Dürrschnabel, D., Mchedlidze, T., Radermacher, M., Wulf, L.: A Greedy Heuristic for Crossing-Angle Maximization. In: Biedl, T.C. and Kerren, A. (eds.) Graph Drawing. pp. 286–299. Springer (2018).
@inproceedings{conf/gd/DemelDMRW18,
author = {Demel, Almut and Dürrschnabel, Dominik and Mchedlidze, Tamara and Radermacher, Marcel and Wulf, Lasse},
booktitle = {Graph Drawing},
crossref = {conf/gd/2018},
editor = {Biedl, Therese C. and Kerren, Andreas},
keywords = {greedy_heuristik},
pages = {286-299},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {A Greedy Heuristic for Crossing-Angle Maximization.},
volume = 11282,
year = 2018
}%0 Conference Paper
%1 conf/gd/DemelDMRW18
%A Demel, Almut
%A Dürrschnabel, Dominik
%A Mchedlidze, Tamara
%A Radermacher, Marcel
%A Wulf, Lasse
%B Graph Drawing
%D 2018
%E Biedl, Therese C.
%E Kerren, Andreas
%I Springer
%P 286-299
%T A Greedy Heuristic for Crossing-Angle Maximization.
%U http://dblp.uni-trier.de/db/conf/gd/gd2018.html#DemelDMRW18
%V 11282
%@ 978-3-030-04414-5 - 1.Atzmueller, M., Thiele, L., Stumme, G., Kauffeld, S.: {Analyzing Group Interaction on Networks of Face-to-Face Proximity using Wearable Sensors}. In: Proc. IEEE International Conference on Future IoT Technologies. IEEE Press, Boston, MA, USA (2018).
@inproceedings{ATSK:18,
address = {Boston, MA, USA},
author = {Atzmueller, Martin and Thiele, Lisa and Stumme, Gerd and Kauffeld, Simone},
booktitle = {Proc. IEEE International Conference on Future IoT Technologies},
keywords = {behavior},
publisher = {IEEE Press},
title = {{Analyzing Group Interaction on Networks of Face-to-Face Proximity using Wearable Sensors}},
year = 2018
}%0 Conference Paper
%1 ATSK:18
%A Atzmueller, Martin
%A Thiele, Lisa
%A Stumme, Gerd
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%B Proc. IEEE International Conference on Future IoT Technologies
%C Boston, MA, USA
%D 2018
%I IEEE Press
%T {Analyzing Group Interaction on Networks of Face-to-Face Proximity using Wearable Sensors}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2018-FutureIoT-Atzmueller-DSNA.pdf - 1.Hanika, T., Zumbrägel, J.: Towards Collaborative Conceptual Exploration. In: Chapman, P., Endres, D., and Pernelle, N. (eds.) ICCS. pp. 120–134. Springer (2018). https://doi.org/10.1007/978-3-319-91379-7_10.
@inproceedings{conf/iccs/HanikaZ18,
author = {Hanika, Tom and Zumbrägel, Jens},
booktitle = {ICCS},
crossref = {conf/iccs/2018},
editor = {Chapman, Peter and Endres, Dominik and Pernelle, Nathalie},
keywords = {itegpub},
pages = {120-134},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Towards Collaborative Conceptual Exploration.},
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%A Zumbrägel, Jens
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%R 10.1007/978-3-319-91379-7_10
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%U http://dblp.uni-trier.de/db/conf/iccs/iccs2018.html#HanikaZ18
%V 10872
%@ 978-3-319-91379-7 - 1.Schmidt, A., Stumme, G.: Prominence and Dominance in Networks. In: Faron Zucker, C., Ghidini, C., Napoli, A., and Yannick, T. (eds.) Proceedings of the 21th International Conference on Knowledge Engineering and Knowledge Management (EKAW). pp. 370–385. Springer (2018).
@inproceedings{schmidt2018prominence,
author = {Schmidt, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 21th International Conference on Knowledge Engineering and Knowledge Management (EKAW)},
editor = {Faron Zucker, Catherine and Ghidini, Chiara and Napoli, Amedeo and Yannick, Toussaint},
keywords = {topographic},
pages = {370-385},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Prominence and Dominance in Networks},
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%1 schmidt2018prominence
%A Schmidt, Andreas
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%B Proceedings of the 21th International Conference on Knowledge Engineering and Knowledge Management (EKAW)
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%E Ghidini, Chiara
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%E Yannick, Toussaint
%I Springer
%P 370-385
%T Prominence and Dominance in Networks
2017
- 1.Loreto, V., Haklay, M., Hotho, A., Servedio, V.C.P., Stumme, G., Theunis, J., Tria, F. eds.: Participatory sensing, opinions and collective awareness. Springer (2017).
@book{loreto2017participatory,
editor = {Loreto, Vittorio and Haklay, Mordechai and Hotho, Andreas and Servedio, Vito C. P. and Stumme, Gerd and Theunis, Jan and Tria, Francesca},
keywords = {myown},
publisher = {Springer},
title = {Participatory sensing, opinions and collective awareness},
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}%0 Book
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%E Loreto, Vittorio
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%E Stumme, Gerd
%E Theunis, Jan
%E Tria, Francesca
%I Springer
%T Participatory sensing, opinions and collective awareness
%@ 9783319256580 3319256580 - 1.Atzmueller, M., Sternberg, E.: {Mixed-Initiative Feature Engineering Using Knowledge Graphs}. In: Proc. 9th International Conference on Knowledge Capture (K-CAP). ACM Press, New York, NY, USA (2017).
@inproceedings{AS:17,
address = {New York, NY, USA},
author = {Atzmueller, Martin and Sternberg, Eric},
booktitle = {Proc. 9th International Conference on Knowledge Capture (K-CAP)},
keywords = {itegpub},
month = {(accepted)},
publisher = {ACM Press},
title = {{Mixed-Initiative Feature Engineering Using Knowledge Graphs}},
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%T {Mixed-Initiative Feature Engineering Using Knowledge Graphs}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-kcap.pdf - 1.Atzmueller, M., Becker, M., Molino, A., Mueller, J., Peters, J., Sirbu, A.: {Applications for Environmental Sensing in EveryAware}. In: Loreto, V., Haklay, M., Hotho, A., Servedio, V.D., Stumme, G., Tria, F., and Theunis, J. (eds.) Participatory Sensing, Opinions and Collective Awareness. Springer Verlag, Heidelberg, Germany (2017).
@incollection{ABMMPS:16,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin and Becker, Martin and Molino, Andrea and Mueller, Juergen and Peters, Jan and Sirbu, Alina},
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editor = {Loreto, Vittorio and Haklay, Muki and Hotho, Andreas and Servedio, Vito D.P. and Stumme, Gerd and Tria, Francesca and Theunis, Jan},
keywords = {analysis},
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title = {{Applications for Environmental Sensing in EveryAware}},
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}%0 Book Section
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%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-EveryAware-Book-part_I_ch_7_Atzmueller.pdf - 1.Atzmueller, M., Becker, M., Mueller, J.: {Collective Sensing Platforms}. In: Loreto, V., Haklay, M., Hotho, A., Servedio, V.D., Stumme, G., Tria, F., and Theunis, J. (eds.) Participatory Sensing, Opinions and Collective Awareness. Springer Verlag, Heidelberg, Germany (2017).
@incollection{ABM:16,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin and Becker, Martin and Mueller, Juergen},
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%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-EveryAware-Book-part_I_ch_6_Atzmueller.pdf - 1.Atzmueller, M., Thiele, L., Stumme, G., Kauffeld, S.: {Contact Patterns, Group Interaction and Dynamics on Socio-Behavioral Multiplex Networks}. In: Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017). Eindhoven University of Technology, Eindhoven, The Netherlands (2017).
@inproceedings{ATSK:17,
address = {Eindhoven, The Netherlands},
author = {Atzmueller, Martin and Thiele, Lisa and Stumme, Gerd and Kauffeld, Simone},
booktitle = {Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017)},
keywords = {contacts},
publisher = {Eindhoven University of Technology},
title = {{Contact Patterns, Group Interaction and Dynamics on Socio-Behavioral Multiplex Networks}},
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%A Stumme, Gerd
%A Kauffeld, Simone
%B Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017)
%C Eindhoven, The Netherlands
%D 2017
%I Eindhoven University of Technology
%T {Contact Patterns, Group Interaction and Dynamics on Socio-Behavioral Multiplex Networks}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-bl-connectu-preprint.pdf - 1.Borchmann, D., Hanika, T., Obiedkov, S.: On the Usability of Probably Approximately Correct Implication Bases. CoRR. abs/1701.00877, (2017).
@article{journals/corr/BorchmannHO17,
author = {Borchmann, Daniel and Hanika, Tom and Obiedkov, Sergei},
journal = {CoRR},
keywords = {implications},
title = {On the Usability of Probably Approximately Correct Implication Bases.},
volume = {abs/1701.00877},
year = 2017
}%0 Journal Article
%1 journals/corr/BorchmannHO17
%A Borchmann, Daniel
%A Hanika, Tom
%A Obiedkov, Sergei
%D 2017
%J CoRR
%T On the Usability of Probably Approximately Correct Implication Bases.
%U http://dblp.uni-trier.de/db/journals/corr/corr1701.html#BorchmannHO17
%V abs/1701.00877 - 1.Atzmueller, M.: {Onto Explicative Data Mining: Exploratory, Interpretable and Explainable Analysis}. In: Proc. Dutch-Belgian Database Day. TU Eindhoven, Netherlands (2017).
@inproceedings{Atzmueller:DBDBD17,
author = {Atzmueller, Martin},
booktitle = {Proc. Dutch-Belgian Database Day},
keywords = {explanation-aware},
month = {(accepted)},
organization = {TU Eindhoven, Netherlands},
title = {{Onto Explicative Data Mining: Exploratory, Interpretable and Explainable Analysis}},
year = 2017
}%0 Conference Paper
%1 Atzmueller:DBDBD17
%A Atzmueller, Martin
%B Proc. Dutch-Belgian Database Day
%D 2017
%T {Onto Explicative Data Mining: Exploratory, Interpretable and Explainable Analysis}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-dbdbd-preprint.pdf - 1.Atzmueller, M., Schmidt, A., Kloepper, B., Arnu, D.: {HypGraphs: An Approach for Analysis and Assessment of Graph-Based and Sequential Hypotheses}. In: New Frontiers in Mining Complex Patterns. Postproceedings NFMCP 2016. Springer Verlag, Berlin/Heidelberg, Germany (2017).
@inproceedings{ASKA:17,
address = {Berlin/Heidelberg, Germany},
author = {Atzmueller, Martin and Schmidt, Andreas and Kloepper, Benjamin and Arnu, David},
booktitle = {New Frontiers in Mining Complex Patterns. Postproceedings NFMCP 2016},
keywords = {sequential},
month = {(In Press)},
publisher = {Springer Verlag},
series = {LNAI},
title = {{HypGraphs: An Approach for Analysis and Assessment of Graph-Based and Sequential Hypotheses}},
year = 2017
}%0 Conference Paper
%1 ASKA:17
%A Atzmueller, Martin
%A Schmidt, Andreas
%A Kloepper, Benjamin
%A Arnu, David
%B New Frontiers in Mining Complex Patterns. Postproceedings NFMCP 2016
%C Berlin/Heidelberg, Germany
%D 2017
%I Springer Verlag
%T {HypGraphs: An Approach for Analysis and Assessment of Graph-Based and Sequential Hypotheses}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/Atzmueller-Hypgraphs-NFMCP2016-PP.pdf - 1.Mueller, J., Stumme, G.: Predicting Rising Follower Counts on Twitter Using Profile Information. In: 9th International ACM Web Science Conference 2017 (WebSci 2017), Troy, NY, USA, June 26-28, 2017. Accepted for Publication. ACM, New York, NY, USA (2017). https://doi.org/10.1145/3091478.3091490.When evaluating the cause of one's popularity on Twitter, one thing is considered to be the main driver: Many tweets. There is debate about the kind of tweet one should publish, but little beyond tweets. Of particular interest is the information provided by each Twitter user's profile page. One of the features are the given names on those profiles. Studies on psychology and economics identified correlations of the first name to, e.g., one's school marks or chances of getting a job interview in the US. Therefore, we are interested in the influence of those profile information on the follower count. We addressed this question by analyzing the profiles of about 6 Million Twitter users. All profiles are separated into three groups: Users that have a first name, English words, or neither of both in their name field. The assumption is that names and words influence the discoverability of a user and subsequently his/her follower count. We propose a classifier that labels users who will increase their follower count within a month by applying different models based on the user's group. The classifiers are evaluated with the area under the receiver operator curve score and achieves a score above 0.800.
@inproceedings{mueller-2017,
abstract = {When evaluating the cause of one's popularity on Twitter, one thing is considered to be the main driver: Many tweets. There is debate about the kind of tweet one should publish, but little beyond tweets. Of particular interest is the information provided by each Twitter user's profile page. One of the features are the given names on those profiles. Studies on psychology and economics identified correlations of the first name to, e.g., one's school marks or chances of getting a job interview in the US. Therefore, we are interested in the influence of those profile information on the follower count. We addressed this question by analyzing the profiles of about 6 Million Twitter users. All profiles are separated into three groups: Users that have a first name, English words, or neither of both in their name field. The assumption is that names and words influence the discoverability of a user and subsequently his/her follower count. We propose a classifier that labels users who will increase their follower count within a month by applying different models based on the user's group. The classifiers are evaluated with the area under the receiver operator curve score and achieves a score above 0.800.},
address = {New York, NY, USA},
author = {Mueller, Juergen and Stumme, Gerd},
booktitle = {9th International ACM Web Science Conference 2017 (WebSci 2017), Troy, NY, USA, June 26-28, 2017. Accepted for Publication},
keywords = {KDE},
month = {06},
publisher = {ACM},
title = {Predicting Rising Follower Counts on Twitter Using Profile Information},
year = 2017
}%0 Conference Paper
%1 mueller-2017
%A Mueller, Juergen
%A Stumme, Gerd
%B 9th International ACM Web Science Conference 2017 (WebSci 2017), Troy, NY, USA, June 26-28, 2017. Accepted for Publication
%C New York, NY, USA
%D 2017
%I ACM
%R 10.1145/3091478.3091490
%T Predicting Rising Follower Counts on Twitter Using Profile Information
%U http://dx.doi.org/10.1145/3091478.3091490
%X When evaluating the cause of one's popularity on Twitter, one thing is considered to be the main driver: Many tweets. There is debate about the kind of tweet one should publish, but little beyond tweets. Of particular interest is the information provided by each Twitter user's profile page. One of the features are the given names on those profiles. Studies on psychology and economics identified correlations of the first name to, e.g., one's school marks or chances of getting a job interview in the US. Therefore, we are interested in the influence of those profile information on the follower count. We addressed this question by analyzing the profiles of about 6 Million Twitter users. All profiles are separated into three groups: Users that have a first name, English words, or neither of both in their name field. The assumption is that names and words influence the discoverability of a user and subsequently his/her follower count. We propose a classifier that labels users who will increase their follower count within a month by applying different models based on the user's group. The classifiers are evaluated with the area under the receiver operator curve score and achieves a score above 0.800.
%@ 978-1-4503-4896-6 - 1.Kibanov, M., Stumme, G., Amin, I., Lee, J.G.: Mining social media to inform peatland fire and haze disaster management. Social Network Analysis and Mining. 7, 30 (2017). https://doi.org/10.1007/s13278-017-0446-1.Peatland fires and haze events are disasters with national, regional, and international implications. The phenomena lead to direct damage to local assets, as well as broader economic and environmental losses. Satellite imagery is still the main and often the only available source of information for disaster management. In this article, we test the potential of social media to assist disaster management. To this end, we compare insights from two datasets: fire hotspots detected via NASA satellite imagery and almost all GPS-stamped tweets from Sumatra Island, Indonesia, posted during 2014. Sumatra Island is chosen as it regularly experiences a significant number of haze events, which affect citizens in Indonesia as well as in nearby countries including Malaysia and Singapore. We analyze temporal correlations between the datasets and their geo-spatial interdependence. Furthermore, we show how Twitter data reveal changes in users' behavior during severe haze events. Overall, we demonstrate that social media are a valuable source of complementary and supplementary information for haze disaster management. Based on our methodology and findings, an analytics tool to improve peatland fire and haze disaster management by the Indonesian authorities is under development.
@article{kibanov2017mining,
abstract = {Peatland fires and haze events are disasters with national, regional, and international implications. The phenomena lead to direct damage to local assets, as well as broader economic and environmental losses. Satellite imagery is still the main and often the only available source of information for disaster management. In this article, we test the potential of social media to assist disaster management. To this end, we compare insights from two datasets: fire hotspots detected via NASA satellite imagery and almost all GPS-stamped tweets from Sumatra Island, Indonesia, posted during 2014. Sumatra Island is chosen as it regularly experiences a significant number of haze events, which affect citizens in Indonesia as well as in nearby countries including Malaysia and Singapore. We analyze temporal correlations between the datasets and their geo-spatial interdependence. Furthermore, we show how Twitter data reveal changes in users' behavior during severe haze events. Overall, we demonstrate that social media are a valuable source of complementary and supplementary information for haze disaster management. Based on our methodology and findings, an analytics tool to improve peatland fire and haze disaster management by the Indonesian authorities is under development.},
author = {Kibanov, Mark and Stumme, Gerd and Amin, Imaduddin and Lee, Jong Gun},
journal = {Social Network Analysis and Mining},
keywords = 2017,
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title = {Mining social media to inform peatland fire and haze disaster management},
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}%0 Journal Article
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%A Stumme, Gerd
%A Amin, Imaduddin
%A Lee, Jong Gun
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%J Social Network Analysis and Mining
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%R 10.1007/s13278-017-0446-1
%T Mining social media to inform peatland fire and haze disaster management
%U http://rdcu.be/udmt
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%X Peatland fires and haze events are disasters with national, regional, and international implications. The phenomena lead to direct damage to local assets, as well as broader economic and environmental losses. Satellite imagery is still the main and often the only available source of information for disaster management. In this article, we test the potential of social media to assist disaster management. To this end, we compare insights from two datasets: fire hotspots detected via NASA satellite imagery and almost all GPS-stamped tweets from Sumatra Island, Indonesia, posted during 2014. Sumatra Island is chosen as it regularly experiences a significant number of haze events, which affect citizens in Indonesia as well as in nearby countries including Malaysia and Singapore. We analyze temporal correlations between the datasets and their geo-spatial interdependence. Furthermore, we show how Twitter data reveal changes in users' behavior during severe haze events. Overall, we demonstrate that social media are a valuable source of complementary and supplementary information for haze disaster management. Based on our methodology and findings, an analytics tool to improve peatland fire and haze disaster management by the Indonesian authorities is under development. - 1.Thiele, L., Sauer, N.C., Atzmueller, M., Kauffeld, S.: {The Co-Evolution of Career Aspirations and Peer Relationships in Psychology Bachelor Students: A Longitudinal Social Network Study}. Journal of Vocational Behavior. (2017).
@article{TSAK:2017,
author = {Thiele, Lisa and Sauer, Nils Christian and Atzmueller, Martin and Kauffeld, Simone},
journal = {Journal of Vocational Behavior},
keywords = {longitudinal},
title = {{The Co-Evolution of Career Aspirations and Peer Relationships in Psychology Bachelor Students: A Longitudinal Social Network Study}},
year = 2017
}%0 Journal Article
%1 TSAK:2017
%A Thiele, Lisa
%A Sauer, Nils Christian
%A Atzmueller, Martin
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%J Journal of Vocational Behavior
%T {The Co-Evolution of Career Aspirations and Peer Relationships in Psychology Bachelor Students: A Longitudinal Social Network Study}
%U https://www.sciencedirect.com/science/article/abs/pii/S0001879117301665 - 1.Gautama, S., Atzmueller, M., Kostakos, V., Gillis, D., Hosio, S.: {Observing Human Activity Through Sensing}. In: Loreto, V., Haklay, M., Hotho, A., Servedio, V.D., Stumme, G., Tria, F., and Theunis, J. (eds.) Participatory Sensing, Opinions and Collective Awareness. Springer Verlag, Heidelberg, Germany (2017).
@incollection{GAKGH:16,
address = {Heidelberg, Germany},
author = {Gautama, Sidharta and Atzmueller, Martin and Kostakos, Vasillis and Gillis, Dominique and Hosio, Simo},
booktitle = {Participatory Sensing, Opinions and Collective Awareness},
editor = {Loreto, Vittorio and Haklay, Muki and Hotho, Andreas and Servedio, Vito D.P. and Stumme, Gerd and Tria, Francesca and Theunis, Jan},
keywords = {human},
publisher = {Springer Verlag},
title = {{Observing Human Activity Through Sensing}},
year = 2017
}%0 Book Section
%1 GAKGH:16
%A Gautama, Sidharta
%A Atzmueller, Martin
%A Kostakos, Vasillis
%A Gillis, Dominique
%A Hosio, Simo
%B Participatory Sensing, Opinions and Collective Awareness
%C Heidelberg, Germany
%D 2017
%E Loreto, Vittorio
%E Haklay, Muki
%E Hotho, Andreas
%E Servedio, Vito D.P.
%E Stumme, Gerd
%E Tria, Francesca
%E Theunis, Jan
%I Springer Verlag
%T {Observing Human Activity Through Sensing}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-EveryAware-Book-part_I_ch_3_Gautama.pdf - 1.Folmer, J., Kirchen, I., Trunzer, E., Vogel-Heuser, B., Pötter, T., Graube, M., Heinze, S., Urbas, L., Atzmueller, M., Arnu, D.: {Challenges for Big and Smart Data in Process Industries}. atp edition. 01-02, (2017).
@article{SmartData:ATP:2017,
author = {Folmer, Jens and Kirchen, Iris and Trunzer, Emanuel and Vogel-Heuser, Birgit and Pötter, Thorsten and Graube, Markus and Heinze, Sebastian and Urbas, Leon and Atzmueller, Martin and Arnu, David},
journal = {atp edition},
keywords = {smart},
title = {{Challenges for Big and Smart Data in Process Industries}},
volume = {01-02},
year = 2017
}%0 Journal Article
%1 SmartData:ATP:2017
%A Folmer, Jens
%A Kirchen, Iris
%A Trunzer, Emanuel
%A Vogel-Heuser, Birgit
%A Pötter, Thorsten
%A Graube, Markus
%A Heinze, Sebastian
%A Urbas, Leon
%A Atzmueller, Martin
%A Arnu, David
%D 2017
%J atp edition
%T {Challenges for Big and Smart Data in Process Industries}
%V 01-02 - 1.Borchmann, D., Hanika, T.: Individuality in Social Networks. In: Missaoui, R., Kuznetsov, S.O., and Obiedkov, S. (eds.) Formal Concept Analysis of Social Networks. pp. 19–40. Springer International Publishing, Cham (2017). https://doi.org/10.1007/978-3-319-64167-6_2.We consider individuality in bi-modal social networks, a facet that has not been considered before in the mathematical analysis of social networks. We use methods from formal concept analysis to develop a natural definition for individuality, and provide experimental evidence that this yields a meaningful approach for additional insights into the nature of social networks.
@inbook{Borchmann2017,
abstract = {We consider individuality in bi-modal social networks, a facet that has not been considered before in the mathematical analysis of social networks. We use methods from formal concept analysis to develop a natural definition for individuality, and provide experimental evidence that this yields a meaningful approach for additional insights into the nature of social networks.},
address = {Cham},
author = {Borchmann, Daniel and Hanika, Tom},
booktitle = {Formal Concept Analysis of Social Networks},
editor = {Missaoui, Rokia and Kuznetsov, Sergei O. and Obiedkov, Sergei},
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%T Individuality in Social Networks
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%X We consider individuality in bi-modal social networks, a facet that has not been considered before in the mathematical analysis of social networks. We use methods from formal concept analysis to develop a natural definition for individuality, and provide experimental evidence that this yields a meaningful approach for additional insights into the nature of social networks.
%@ 978-3-319-64167-6 - 1.Hanika, T., Zumbrägel, J.: Towards Collaborative Conceptual Exploration. CoRR. abs/1712.08858, (2017).
@article{journals/corr/abs-1712-08858,
author = {Hanika, Tom and Zumbrägel, Jens},
journal = {CoRR},
keywords = {kde},
title = {Towards Collaborative Conceptual Exploration.},
volume = {abs/1712.08858},
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}%0 Journal Article
%1 journals/corr/abs-1712-08858
%A Hanika, Tom
%A Zumbrägel, Jens
%D 2017
%J CoRR
%T Towards Collaborative Conceptual Exploration.
%U http://dblp.uni-trier.de/db/journals/corr/corr1712.html#abs-1712-08858
%V abs/1712.08858 - 1.Knoell, D., Atzmueller, M., Rieder, C., Scherer, K.P.: {A Scalable Framework for Data-Driven Ontology Evaluation}. In: Proc. GWEM 2017, co-located with 9th Conference Professional Knowledge Management (WM 2017). KIT, Karlsruhe, Germany (2017).
@inproceedings{KARS:17:GWEM,
address = {Karlsruhe, Germany},
author = {Knoell, Daniel and Atzmueller, Martin and Rieder, Constantin and Scherer, Klaus Peter},
booktitle = {Proc. GWEM 2017, co-located with 9th Conference Professional Knowledge Management (WM 2017)},
keywords = {ontology},
publisher = {KIT},
title = {{A Scalable Framework for Data-Driven Ontology Evaluation}},
year = 2017
}%0 Conference Paper
%1 KARS:17:GWEM
%A Knoell, Daniel
%A Atzmueller, Martin
%A Rieder, Constantin
%A Scherer, Klaus Peter
%B Proc. GWEM 2017, co-located with 9th Conference Professional Knowledge Management (WM 2017)
%C Karlsruhe, Germany
%D 2017
%I KIT
%T {A Scalable Framework for Data-Driven Ontology Evaluation}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/Knoell-GWEM2017-Preprint.pdf - 1.Kanawati, R., Atzmueller, M.: {Mining Attributed Networks}, https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-dsaa17-abstract.pdf, (2017).
@misc{RA:17:DSAA,
author = {Kanawati, Rushed and Atzmueller, Martin},
howpublished = {DSAA 2017, Tutorial Abstract},
keywords = {itegpub},
title = {{Mining Attributed Networks}},
year = 2017
}%0 Generic
%1 RA:17:DSAA
%A Kanawati, Rushed
%A Atzmueller, Martin
%D 2017
%T {Mining Attributed Networks}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-dsaa17-abstract.pdf - 1.Atzmueller, M.: {Community Detection and Analysis on Attributed Social Networks}. In: Encyclopedia of Social Network Analysis and Mining. Springer, Heidelberg, Germany (2017).
@incollection{Atzmueller:17:ESNAM,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin},
booktitle = {Encyclopedia of Social Network Analysis and Mining},
keywords = {iteg},
publisher = {Springer},
title = {{Community Detection and Analysis on Attributed Social Networks}},
year = 2017
}%0 Book Section
%1 Atzmueller:17:ESNAM
%A Atzmueller, Martin
%B Encyclopedia of Social Network Analysis and Mining
%C Heidelberg, Germany
%D 2017
%I Springer
%T {Community Detection and Analysis on Attributed Social Networks}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-community-detection-analysis-attributed-networks-esnam-preprint.pdf - 1.Atzmueller, M., Hayat, N., Schmidt, A., Klöpper, B.: {Explanation-Aware Feature Selection using Symbolic Time Series Abstraction: Approaches and Experiences in a Petro-Chemical Production Context}. In: Proc. IEEE International Conference on Industrial Informatics (INDIN). IEEE Press, Boston, MA, USA (2017).
@inproceedings{AHSK:17,
address = {Boston, MA, USA},
author = {Atzmueller, Martin and Hayat, Naveed and Schmidt, Andreas and Klöpper, Benjamin},
booktitle = {Proc. IEEE International Conference on Industrial Informatics (INDIN)},
keywords = {feepub},
publisher = {IEEE Press},
title = {{Explanation-Aware Feature Selection using Symbolic Time Series Abstraction: Approaches and Experiences in a Petro-Chemical Production Context}},
year = 2017
}%0 Conference Paper
%1 AHSK:17
%A Atzmueller, Martin
%A Hayat, Naveed
%A Schmidt, Andreas
%A Klöpper, Benjamin
%B Proc. IEEE International Conference on Industrial Informatics (INDIN)
%C Boston, MA, USA
%D 2017
%I IEEE Press
%T {Explanation-Aware Feature Selection using Symbolic Time Series Abstraction: Approaches and Experiences in a Petro-Chemical Production Context}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-indin-preprint.pdf - 1.Atzmueller, M., Arnu, D., Schmidt, A.: {Anomaly Analytics and Structural Assessment in Process Industries}. In: Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017). Eindhoven University of Technology, Eindhoven, The Netherlands (2017).
@inproceedings{AAS:17a,
address = {Eindhoven, The Netherlands},
author = {Atzmueller, Martin and Arnu, David and Schmidt, Andreas},
booktitle = {Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017)},
keywords = {hypgraphs},
publisher = {Eindhoven University of Technology},
title = {{Anomaly Analytics and Structural Assessment in Process Industries}},
year = 2017
}%0 Conference Paper
%1 AAS:17a
%A Atzmueller, Martin
%A Arnu, David
%A Schmidt, Andreas
%B Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017)
%C Eindhoven, The Netherlands
%D 2017
%I Eindhoven University of Technology
%T {Anomaly Analytics and Structural Assessment in Process Industries}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-bl-hypgraphs-preprint.pdf - 1.Atzmueller, M., Arnu, D., Schmidt, A.: {Anomaly Detection and Structural Analysis in Industrial Production Environments}. In: Proc. International Data Science Conference (IDSC 2017). , Salzburg, Austria (2017).
@inproceedings{AAS:17,
address = {Salzburg, Austria},
author = {Atzmueller, Martin and Arnu, David and Schmidt, Andreas},
booktitle = {Proc. International Data Science Conference (IDSC 2017)},
keywords = {feepub},
title = {{Anomaly Detection and Structural Analysis in Industrial Production Environments}},
year = 2017
}%0 Conference Paper
%1 AAS:17
%A Atzmueller, Martin
%A Arnu, David
%A Schmidt, Andreas
%B Proc. International Data Science Conference (IDSC 2017)
%C Salzburg, Austria
%D 2017
%T {Anomaly Detection and Structural Analysis in Industrial Production Environments}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-idsc-preprint.pdf - 1.Atzmueller, M.: {Exceptional Model Mining in Ubiquitous and Social Environments}. In: Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017). Eindhoven University of Technology, Eindhoven, The Netherlands (2017).
@inproceedings{Atzmueller:17,
address = {Eindhoven, The Netherlands},
author = {Atzmueller, Martin},
booktitle = {Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017)},
keywords = {hypgraphs},
publisher = {Eindhoven University of Technology},
title = {{Exceptional Model Mining in Ubiquitous and Social Environments}},
year = 2017
}%0 Conference Paper
%1 Atzmueller:17
%A Atzmueller, Martin
%B Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017)
%C Eindhoven, The Netherlands
%D 2017
%I Eindhoven University of Technology
%T {Exceptional Model Mining in Ubiquitous and Social Environments}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-bl-emm-muse-preprint.pdf - 1.Atzmueller, M.: {Descriptive Community Detection}. In: Missaoui, R., Obiedkov, S., and Kuznetsov, S. (eds.) Formal Concept Analysis in Social Network Analysis. Springer Verlag, Berlin/Heidelberg, Germany (2017).
@incollection{Atzmueller:17:SNA:DCD,
address = {Berlin/Heidelberg, Germany},
author = {Atzmueller, Martin},
booktitle = {Formal Concept Analysis in Social Network Analysis},
editor = {Missaoui, Rokia and Obiedkov, Sergei and Kuznetsov, Sergei},
keywords = {itegpub},
publisher = {Springer Verlag},
title = {{Descriptive Community Detection}},
year = 2017
}%0 Book Section
%1 Atzmueller:17:SNA:DCD
%A Atzmueller, Martin
%B Formal Concept Analysis in Social Network Analysis
%C Berlin/Heidelberg, Germany
%D 2017
%E Missaoui, Rokia
%E Obiedkov, Sergei
%E Kuznetsov, Sergei
%I Springer Verlag
%T {Descriptive Community Detection}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2017-atzmueller-descriptive-community-detection.pdf
2016
- 1.Knoell, D., Atzmueller, M., Rieder, C., Scherer, K.P.: {BISHOP – Big Data Driven Self-Learning Support for High-performance Ontology Population}. In: Proc. LWA 2016 (FGWM Special Track). University of Potsdam, Potsdam, Germany (2016).
@inproceedings{KARS:16:LWDA,
address = {Potsdam, Germany},
author = {Knoell, Daniel and Atzmueller, Martin and Rieder, Constantin and Scherer, Klaus Peter},
booktitle = {Proc. LWA 2016 (FGWM Special Track)},
keywords = {ontology},
publisher = {University of Potsdam},
title = {{BISHOP – Big Data Driven Self-Learning Support for High-performance Ontology Population}},
year = 2016
}%0 Conference Paper
%1 KARS:16:LWDA
%A Knoell, Daniel
%A Atzmueller, Martin
%A Rieder, Constantin
%A Scherer, Klaus Peter
%B Proc. LWA 2016 (FGWM Special Track)
%C Potsdam, Germany
%D 2016
%I University of Potsdam
%T {BISHOP – Big Data Driven Self-Learning Support for High-performance Ontology Population}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/BISHOP-LWDA2016.pdf - 1.Niebler, T., Becker, M., Zoller, D., Doerfel, S., Hotho, A.: FolkTrails: Interpreting Navigation Behavior in a Social Tagging System. In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. ACM, New York, NY, USA (2016).Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation.
@inproceedings{niebler2016folktrails,
abstract = {Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation.},
address = {New York, NY, USA},
author = {Niebler, Thomas and Becker, Martin and Zoller, Daniel and Doerfel, Stephan and Hotho, Andreas},
booktitle = {Proceedings of the 25th ACM International on Conference on Information and Knowledge Management},
keywords = {bibsonomy},
note = {forthcoming},
publisher = {ACM},
series = {CIKM '16},
title = {FolkTrails: Interpreting Navigation Behavior in a Social Tagging System},
year = 2016
}%0 Conference Paper
%1 niebler2016folktrails
%A Niebler, Thomas
%A Becker, Martin
%A Zoller, Daniel
%A Doerfel, Stephan
%A Hotho, Andreas
%B Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
%C New York, NY, USA
%D 2016
%I ACM
%T FolkTrails: Interpreting Navigation Behavior in a Social Tagging System
%U http://dx.doi.org/10.1145/2983323.2983686
%X Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation. - 1.Borchmann, D., Hanika, T.: Some Experimental Results on Randomly Generating Formal Contexts. In: Huchard, M. and Kuznetsov, S. (eds.) CLA. pp. 57–69. CEUR-WS.org (2016).
@inproceedings{conf/cla/BorchmannH16,
author = {Borchmann, Daniel and Hanika, Tom},
booktitle = {CLA},
crossref = {conf/cla/2016},
editor = {Huchard, Marianne and Kuznetsov, Sergei},
keywords = {itegpub},
pages = {57-69},
publisher = {CEUR-WS.org},
series = {CEUR Workshop Proceedings},
title = {Some Experimental Results on Randomly Generating Formal Contexts.},
volume = 1624,
year = 2016
}%0 Conference Paper
%1 conf/cla/BorchmannH16
%A Borchmann, Daniel
%A Hanika, Tom
%B CLA
%D 2016
%E Huchard, Marianne
%E Kuznetsov, Sergei
%I CEUR-WS.org
%P 57-69
%T Some Experimental Results on Randomly Generating Formal Contexts.
%U http://dblp.uni-trier.de/db/conf/cla/cla2016.html#BorchmannH16
%V 1624 - 1.Atzmueller, M.: {Advances in Exploratory Pattern Analytics on Ubiquitous Data and Social Media}. In: Michaelis, S., Piatkowski, N., and Stolpe, M. (eds.) Solving Large Scale Learning Tasks: Challenges and Algorithms. Festschrift in Honour of Prof. Dr. Katharina Morik. Springer Verlag (2016).
@incollection{Atzmueller:16m,
author = {Atzmueller, Martin},
booktitle = {Solving Large Scale Learning Tasks: Challenges and Algorithms. Festschrift in Honour of Prof. Dr. Katharina Morik},
editor = {Michaelis, Stefan and Piatkowski, Nico and Stolpe, Marco},
keywords = 2016,
publisher = {Springer Verlag},
series = {LNCS},
title = {{Advances in Exploratory Pattern Analytics on Ubiquitous Data and Social Media}},
volume = 9580,
year = 2016
}%0 Book Section
%1 Atzmueller:16m
%A Atzmueller, Martin
%B Solving Large Scale Learning Tasks: Challenges and Algorithms. Festschrift in Honour of Prof. Dr. Katharina Morik
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%E Michaelis, Stefan
%E Piatkowski, Nico
%E Stolpe, Marco
%I Springer Verlag
%T {Advances in Exploratory Pattern Analytics on Ubiquitous Data and Social Media}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-atzmueller-advances-in-exploratory-pattern-analytics.pdf
%V 9580 - 1.Klöpper, B., Dix, M., Schorer, L., Ampofo, A., Atzmueller, M., Arnu, D., Klinkenberg, R.: {Defining Software Architectures for Big Data Enabled Operator Support Systems}. In: Proc. IEEE International Conference on Industrial Informatics (INDIN). IEEE Press, Boston, MA, USA (2016).
@inproceedings{KloepperEtAl:INDIN:2016,
address = {Boston, MA, USA},
author = {Klöpper, Benjamin and Dix, Marcel and Schorer, Lukas and Ampofo, Ann and Atzmueller, Martin and Arnu, David and Klinkenberg, Ralf},
booktitle = {Proc. IEEE International Conference on Industrial Informatics (INDIN)},
keywords = {itegpub},
publisher = {IEEE Press},
title = {{Defining Software Architectures for Big Data Enabled Operator Support Systems}},
year = 2016
}%0 Conference Paper
%1 KloepperEtAl:INDIN:2016
%A Klöpper, Benjamin
%A Dix, Marcel
%A Schorer, Lukas
%A Ampofo, Ann
%A Atzmueller, Martin
%A Arnu, David
%A Klinkenberg, Ralf
%B Proc. IEEE International Conference on Industrial Informatics (INDIN)
%C Boston, MA, USA
%D 2016
%I IEEE Press
%T {Defining Software Architectures for Big Data Enabled Operator Support Systems}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/DefiningSoftwareArchitecturesForBigDataEnabledOSS_INDIN2016Preprint.pdf - 1.Atzmueller, M., Fries, B., Hayat, N.: {Sensing, Processing and Analytics - Augmenting the Ubicon Platform for Anticipatory Ubiquitous Computing}. In: Proc. ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication. ACM Press, New York, NY, USA (2016).
@inproceedings{AFH:16,
address = {New York, NY, USA},
author = {Atzmueller, Martin and Fries, Björn and Hayat, Naveed},
booktitle = {Proc. ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication},
keywords = {ubicon},
publisher = {ACM Press},
series = {UbiComp '16 Adjunct},
title = {{Sensing, Processing and Analytics - Augmenting the Ubicon Platform for Anticipatory Ubiquitous Computing}},
year = 2016
}%0 Conference Paper
%1 AFH:16
%A Atzmueller, Martin
%A Fries, Björn
%A Hayat, Naveed
%B Proc. ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication
%C New York, NY, USA
%D 2016
%I ACM Press
%T {Sensing, Processing and Analytics - Augmenting the Ubicon Platform for Anticipatory Ubiquitous Computing}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-ubicon-ubicomp16.pdf - 1.Atzmueller, M., Schmidt, A., Arnu, D.: {Sequential Modeling and Structural Anomaly Analytics in Industrial Production Environments}. In: Proc. LWA 2016 (KDML Special Track). University of Potsdam, Potsdam, Germany (2016).
@inproceedings{ASA:16:LWDA,
address = {Potsdam, Germany},
author = {Atzmueller, Martin and Schmidt, Andreas and Arnu, David},
booktitle = {Proc. LWA 2016 (KDML Special Track)},
keywords = {itegpub},
publisher = {University of Potsdam},
title = {{Sequential Modeling and Structural Anomaly Analytics in Industrial Production Environments}},
year = 2016
}%0 Conference Paper
%1 ASA:16:LWDA
%A Atzmueller, Martin
%A Schmidt, Andreas
%A Arnu, David
%B Proc. LWA 2016 (KDML Special Track)
%C Potsdam, Germany
%D 2016
%I University of Potsdam
%T {Sequential Modeling and Structural Anomaly Analytics in Industrial Production Environments}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-atzmueller-anomaly-analytics-lwda.pdf - 1.Mueller, J., Stumme, G.: Gender Inference using Statistical Name Characteristics in Twitter. In: 5th ASE International Conference on Social Informatics (SocInfo 2016), Union, NJ, USA, August 15-17, 2016. Proceedings. pp. 47:1–47:8. ACM, New York, NY, USA (2016). https://doi.org/10.1145/2955129.2955182.Much attention has been given to the task of gender inference of Twitter users. Although names are strong gender indicators, the names of Twitter users are rarely used as a feature; probably due to the high number of ill-formed names, which cannot be found in any name dictionary. Instead of relying solely on a name database, we propose a novel name classifier. Our approach extracts characteristics from the user names and uses those in order to assign the names to a gender. This enables us to classify international first names as well as ill-formed names.
@inproceedings{mueller-2016,
abstract = {Much attention has been given to the task of gender inference of Twitter users. Although names are strong gender indicators, the names of Twitter users are rarely used as a feature; probably due to the high number of ill-formed names, which cannot be found in any name dictionary. Instead of relying solely on a name database, we propose a novel name classifier. Our approach extracts characteristics from the user names and uses those in order to assign the names to a gender. This enables us to classify international first names as well as ill-formed names.},
address = {New York, NY, USA},
author = {Mueller, Juergen and Stumme, Gerd},
booktitle = {5th ASE International Conference on Social Informatics (SocInfo 2016), Union, NJ, USA, August 15-17, 2016. Proceedings},
keywords = {arXiv},
month = {08},
pages = {47:1--47:8},
publisher = {ACM},
title = {Gender Inference using Statistical Name Characteristics in Twitter},
year = 2016
}%0 Conference Paper
%1 mueller-2016
%A Mueller, Juergen
%A Stumme, Gerd
%B 5th ASE International Conference on Social Informatics (SocInfo 2016), Union, NJ, USA, August 15-17, 2016. Proceedings
%C New York, NY, USA
%D 2016
%I ACM
%P 47:1--47:8
%R 10.1145/2955129.2955182
%T Gender Inference using Statistical Name Characteristics in Twitter
%U http://dx.doi.org/10.1145/2955129.2955182
%X Much attention has been given to the task of gender inference of Twitter users. Although names are strong gender indicators, the names of Twitter users are rarely used as a feature; probably due to the high number of ill-formed names, which cannot be found in any name dictionary. Instead of relying solely on a name database, we propose a novel name classifier. Our approach extracts characteristics from the user names and uses those in order to assign the names to a gender. This enables us to classify international first names as well as ill-formed names.
%@ 978-1-4503-4129-5 - 1.Doerfel, S., Jäschke, R., Stumme, G.: The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems. ACM Transactions on Intelligent Systems and Technology. 7, 40:1–40:33 (2016).Social bookmarking systems have established themselves as an important part in today’s web. In such systems, tag recommender systems support users during the posting of a resource by suggesting suitable tags. Tag recommender algorithms have often been evaluated in offline benchmarking experiments. Yet, the particular setup of such experiments has rarely been analyzed. In particular, since the recommendation quality usually suffers from difficulties like the sparsity of the data or the cold start problem for new resources or users, datasets have often been pruned to so-called cores (specific subsets of the original datasets) – however without much consideration of the implications on the benchmarking results. In this paper, we generalize the notion of a core by introducing the new notion of a set-core – which is independent of any graph structure – to overcome a structural drawback in the previous constructions of cores on tagging data. We show that problems caused by some types of cores can be eliminated using setcores. Further, we present a thorough analysis of tag recommender benchmarking setups using cores. To that end, we conduct a large-scale experiment on four real-world datasets in which we analyze the influence of different cores on the evaluation of recommendation algorithms. We can show that the results of the comparison of different recommendation approaches depends on the selection of core type and level. For the benchmarking of tag recommender algorithms, our results suggest that the evaluation must be set up more carefully and should not be based on one arbitrarily chosen core type and level.
@article{doerfel2016cores,
abstract = {Social bookmarking systems have established themselves as an important part in today’s web. In such systems, tag recommender systems support users during the posting of a resource by suggesting suitable tags. Tag recommender algorithms have often been evaluated in offline benchmarking experiments. Yet, the particular setup of such experiments has rarely been analyzed. In particular, since the recommendation quality usually suffers from difficulties like the sparsity of the data or the cold start problem for new resources or users, datasets have often been pruned to so-called cores (specific subsets of the original datasets) – however without much consideration of the implications on the benchmarking results. In this paper, we generalize the notion of a core by introducing the new notion of a set-core – which is independent of any graph structure – to overcome a structural drawback in the previous constructions of cores on tagging data. We show that problems caused by some types of cores can be eliminated using setcores. Further, we present a thorough analysis of tag recommender benchmarking setups using cores. To that end, we conduct a large-scale experiment on four real-world datasets in which we analyze the influence of different cores on the evaluation of recommendation algorithms. We can show that the results of the comparison of different recommendation approaches depends on the selection of core type and level. For the benchmarking of tag recommender algorithms, our results suggest that the evaluation must be set up more carefully and should not be based on one arbitrarily chosen core type and level.},
author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd},
journal = {ACM Transactions on Intelligent Systems and Technology},
keywords = {homepage},
month = {02},
number = 3,
pages = {40:1-40:33},
title = {The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems},
volume = 7,
year = 2016
}%0 Journal Article
%1 doerfel2016cores
%A Doerfel, Stephan
%A Jäschke, Robert
%A Stumme, Gerd
%D 2016
%J ACM Transactions on Intelligent Systems and Technology
%N 3
%P 40:1-40:33
%T The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems
%U http://doi.acm.org/10.1145/2700485
%V 7
%X Social bookmarking systems have established themselves as an important part in today’s web. In such systems, tag recommender systems support users during the posting of a resource by suggesting suitable tags. Tag recommender algorithms have often been evaluated in offline benchmarking experiments. Yet, the particular setup of such experiments has rarely been analyzed. In particular, since the recommendation quality usually suffers from difficulties like the sparsity of the data or the cold start problem for new resources or users, datasets have often been pruned to so-called cores (specific subsets of the original datasets) – however without much consideration of the implications on the benchmarking results. In this paper, we generalize the notion of a core by introducing the new notion of a set-core – which is independent of any graph structure – to overcome a structural drawback in the previous constructions of cores on tagging data. We show that problems caused by some types of cores can be eliminated using setcores. Further, we present a thorough analysis of tag recommender benchmarking setups using cores. To that end, we conduct a large-scale experiment on four real-world datasets in which we analyze the influence of different cores on the evaluation of recommendation algorithms. We can show that the results of the comparison of different recommendation approaches depends on the selection of core type and level. For the benchmarking of tag recommender algorithms, our results suggest that the evaluation must be set up more carefully and should not be based on one arbitrarily chosen core type and level. - 1.Atzmueller, M., Doerfel, S., Mitzlaff, F.: Description-Oriented Community Detection using Exhaustive Subgroup Discovery. Information Sciences. 329, 965–984 (2016). https://doi.org/http://dx.doi.org/10.1016/j.ins.2015.05.008.Abstract Communities can intuitively be defined as subsets of nodes of a graph with a dense structure in the corresponding subgraph. However, for mining such communities usually only structural aspects are taken into account. Typically, no concise nor easily interpretable community description is provided. For tackling this issue, this paper focuses on description-oriented community detection using subgroup discovery. In order to provide both structurally valid and interpretable communities we utilize the graph structure as well as additional descriptive features of the graph’s nodes. A descriptive community pattern built upon these features then describes and identifies a community, i.e., a set of nodes, and vice versa. Essentially, we mine patterns in the “description space” characterizing interesting sets of nodes (i.e., subgroups) in the “graph space”; the interestingness of a community is evaluated by a selectable quality measure. We aim at identifying communities according to standard community quality measures, while providing characteristic descriptions of these communities at the same time. For this task, we propose several optimistic estimates of standard community quality functions to be used for efficient pruning of the search space in an exhaustive branch-and-bound algorithm. We demonstrate our approach in an evaluation using five real-world data sets, obtained from three different social media applications.
@article{atzmueller2015descriptionoriented,
abstract = {Abstract Communities can intuitively be defined as subsets of nodes of a graph with a dense structure in the corresponding subgraph. However, for mining such communities usually only structural aspects are taken into account. Typically, no concise nor easily interpretable community description is provided. For tackling this issue, this paper focuses on description-oriented community detection using subgroup discovery. In order to provide both structurally valid and interpretable communities we utilize the graph structure as well as additional descriptive features of the graph’s nodes. A descriptive community pattern built upon these features then describes and identifies a community, i.e., a set of nodes, and vice versa. Essentially, we mine patterns in the “description space” characterizing interesting sets of nodes (i.e., subgroups) in the “graph space”; the interestingness of a community is evaluated by a selectable quality measure. We aim at identifying communities according to standard community quality measures, while providing characteristic descriptions of these communities at the same time. For this task, we propose several optimistic estimates of standard community quality functions to be used for efficient pruning of the search space in an exhaustive branch-and-bound algorithm. We demonstrate our approach in an evaluation using five real-world data sets, obtained from three different social media applications.},
author = {Atzmueller, Martin and Doerfel, Stephan and Mitzlaff, Folke},
journal = {Information Sciences},
keywords = {inpress},
month = {02},
pages = {965-984},
title = {Description-Oriented Community Detection using Exhaustive Subgroup Discovery},
volume = 329,
year = 2016
}%0 Journal Article
%1 atzmueller2015descriptionoriented
%A Atzmueller, Martin
%A Doerfel, Stephan
%A Mitzlaff, Folke
%D 2016
%J Information Sciences
%P 965-984
%R http://dx.doi.org/10.1016/j.ins.2015.05.008
%T Description-Oriented Community Detection using Exhaustive Subgroup Discovery
%U http://www.sciencedirect.com/science/article/pii/S0020025515003667
%V 329
%X Abstract Communities can intuitively be defined as subsets of nodes of a graph with a dense structure in the corresponding subgraph. However, for mining such communities usually only structural aspects are taken into account. Typically, no concise nor easily interpretable community description is provided. For tackling this issue, this paper focuses on description-oriented community detection using subgroup discovery. In order to provide both structurally valid and interpretable communities we utilize the graph structure as well as additional descriptive features of the graph’s nodes. A descriptive community pattern built upon these features then describes and identifies a community, i.e., a set of nodes, and vice versa. Essentially, we mine patterns in the “description space” characterizing interesting sets of nodes (i.e., subgroups) in the “graph space”; the interestingness of a community is evaluated by a selectable quality measure. We aim at identifying communities according to standard community quality measures, while providing characteristic descriptions of these communities at the same time. For this task, we propose several optimistic estimates of standard community quality functions to be used for efficient pruning of the search space in an exhaustive branch-and-bound algorithm. We demonstrate our approach in an evaluation using five real-world data sets, obtained from three different social media applications. - 1.Doerfel, S., Zoller, D., Singer, P., Niebler, T., Hotho, A., Strohmaier, M.: What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy. ACM Transactions on the Web. 10, 14:1–14:32 (2016). https://doi.org/10.1145/2896821.Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.
@article{doerfel2016users,
abstract = {Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.},
author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
journal = {ACM Transactions on the Web},
keywords = {equality},
month = {05},
number = 2,
pages = {14:1--14:32},
publisher = {ACM},
title = {What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy},
volume = 10,
year = 2016
}%0 Journal Article
%1 doerfel2016users
%A Doerfel, Stephan
%A Zoller, Daniel
%A Singer, Philipp
%A Niebler, Thomas
%A Hotho, Andreas
%A Strohmaier, Markus
%D 2016
%I ACM
%J ACM Transactions on the Web
%N 2
%P 14:1--14:32
%R 10.1145/2896821
%T What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy
%U http://dl.acm.org/citation.cfm?id=2896821
%V 10
%X Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers. - 1.Zoller, D., Doerfel, S., Jäschke, R., Stumme, G., Hotho, A.: Posted, visited, exported: Altmetrics in the social tagging system BibSonomy. Journal of Informetrics. 10, 732–749 (2016). https://doi.org/http://dx.doi.org/10.1016/j.joi.2016.03.005.Abstract In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.
@article{zoller2016posted,
abstract = {Abstract In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.},
author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas},
journal = {Journal of Informetrics},
keywords = {posted},
number = 3,
pages = {732 - 749},
title = {Posted, visited, exported: Altmetrics in the social tagging system BibSonomy},
volume = 10,
year = 2016
}%0 Journal Article
%1 zoller2016posted
%A Zoller, Daniel
%A Doerfel, Stephan
%A Jäschke, Robert
%A Stumme, Gerd
%A Hotho, Andreas
%D 2016
%J Journal of Informetrics
%N 3
%P 732 - 749
%R http://dx.doi.org/10.1016/j.joi.2016.03.005
%T Posted, visited, exported: Altmetrics in the social tagging system BibSonomy
%U http://www.sciencedirect.com/science/article/pii/S1751157715300936
%V 10
%X Abstract In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points. - 1.Gebhardt, J., Froese, T., Krüger, A., Appel, J., Benner, R., Hammer, M., Altermann, A., Hochrein, T., Kugler, C., Jatzkowski, P., Gloy, Y.-S., Saggiomo, M., Roth, R., Elixmann, I., Tapken, H., Weber, W., Atzmueller, M., Garcke, J., Pielmeier, J., Rosen, R., Tercan, H.: {Statusreport: Chancen mit Big Data -- Best Practice}. VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (2016).
@techreport{VDI:Statusreport:2016,
author = {Gebhardt, Jörg and Froese, Thomas and Krüger, Andreas and Appel, Jörg and Benner, Raphael and Hammer, Markus and Altermann, Alexandra and Hochrein, Thomas and Kugler, Christoph and Jatzkowski, Phillip and Gloy, Yves-Simon and Saggiomo, Marco and Roth, Rolf and Elixmann, Inga and Tapken, Heiko and Weber, Wolfgang and Atzmueller, Martin and Garcke, Jochen and Pielmeier, Julia and Rosen, Roland and Tercan, Hasan},
institution = {VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik},
keywords = {itegpub},
title = {{Statusreport: Chancen mit Big Data -- Best Practice}},
year = 2016
}%0 Report
%1 VDI:Statusreport:2016
%A Gebhardt, Jörg
%A Froese, Thomas
%A Krüger, Andreas
%A Appel, Jörg
%A Benner, Raphael
%A Hammer, Markus
%A Altermann, Alexandra
%A Hochrein, Thomas
%A Kugler, Christoph
%A Jatzkowski, Phillip
%A Gloy, Yves-Simon
%A Saggiomo, Marco
%A Roth, Rolf
%A Elixmann, Inga
%A Tapken, Heiko
%A Weber, Wolfgang
%A Atzmueller, Martin
%A Garcke, Jochen
%A Pielmeier, Julia
%A Rosen, Roland
%A Tercan, Hasan
%D 2016
%T {Statusreport: Chancen mit Big Data -- Best Practice}
%U https://m.vdi.de/fileadmin/vdi_de/redakteur_dateien/gma_dateien/z01_NEU_Statusreport_Best_Practice_WEB.pdf - 1.Atzmueller, M., Schmidt, A., Kibanov, M.: {DASHTrails: An Approach for Modeling and Analysis of Distribution-Adapted Sequential Hypotheses and Trails}. In: Proc. WWW 2016 (Companion). IW3C2 / ACM (2016).
@inproceedings{ASK:16,
author = {Atzmueller, Martin and Schmidt, Andreas and Kibanov, Mark},
booktitle = {Proc. WWW 2016 (Companion)},
keywords = {feepub},
organization = {IW3C2 / ACM},
title = {{DASHTrails: An Approach for Modeling and Analysis of Distribution-Adapted Sequential Hypotheses and Trails}},
year = 2016
}%0 Conference Paper
%1 ASK:16
%A Atzmueller, Martin
%A Schmidt, Andreas
%A Kibanov, Mark
%B Proc. WWW 2016 (Companion)
%D 2016
%T {DASHTrails: An Approach for Modeling and Analysis of Distribution-Adapted Sequential Hypotheses and Trails}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-atzmueller-dashtrails.pdf - 1.Atzmueller, M., Hanika, T., Stumme, G., Schaller, R., Ludwig, B.: {Social Event Network Analysis: Structure, Preferences, and Reality}. In: Proc. IEEE/ACM ASONAM. IEEE Press, Boston, MA, USA (2016).
@inproceedings{AHSSL:16:ASONAM,
address = {Boston, MA, USA},
author = {Atzmueller, Martin and Hanika, Tom and Stumme, Gerd and Schaller, Richard and Ludwig, Bernd},
booktitle = {Proc. IEEE/ACM ASONAM},
keywords = {spatial},
publisher = {IEEE Press},
title = {{Social Event Network Analysis: Structure, Preferences, and Reality}},
year = 2016
}%0 Conference Paper
%1 AHSSL:16:ASONAM
%A Atzmueller, Martin
%A Hanika, Tom
%A Stumme, Gerd
%A Schaller, Richard
%A Ludwig, Bernd
%B Proc. IEEE/ACM ASONAM
%C Boston, MA, USA
%D 2016
%I IEEE Press
%T {Social Event Network Analysis: Structure, Preferences, and Reality}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-social-event-analysis-asonam16-preprint.pdf - 1.Atzmueller, M., Mollenhauer, D., Schmidt, A.: {Big Data Analytics Using Local Exceptionality Detection}. In: {Enterprise Big Data Engineering, Analytics, and Management}. IGI Global, Hershey, PA, USA (2016).
@incollection{AMS:16,
address = {Hershey, PA, USA},
author = {Atzmueller, Martin and Mollenhauer, Dennis and Schmidt, Andreas},
booktitle = {{Enterprise Big Data Engineering, Analytics, and Management}},
keywords = {big},
publisher = {IGI Global},
title = {{Big Data Analytics Using Local Exceptionality Detection}},
year = 2016
}%0 Book Section
%1 AMS:16
%A Atzmueller, Martin
%A Mollenhauer, Dennis
%A Schmidt, Andreas
%B {Enterprise Big Data Engineering, Analytics, and Management}
%C Hershey, PA, USA
%D 2016
%I IGI Global
%T {Big Data Analytics Using Local Exceptionality Detection}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/Atzmueller-Preprint-Big-Data-Analytics-Using-Local-Exceptionality-Detection.pdf - 1.Atzmueller, M., Oussena, S., Roth-Berghofer, T. eds.: {Enterprise Big Data Engineering, Analytics and Management}. IGI Global, Hershey, PA, USA (2016).
@book{AOR:16,
address = {Hershey, PA, USA},
editor = {Atzmueller, Martin and Oussena, Samia and Roth-Berghofer, Thomas},
keywords = {big},
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title = {{Enterprise Big Data Engineering, Analytics and Management}},
year = 2016
}%0 Book
%1 AOR:16
%C Hershey, PA, USA
%D 2016
%E Atzmueller, Martin
%E Oussena, Samia
%E Roth-Berghofer, Thomas
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%T {Enterprise Big Data Engineering, Analytics and Management} - 1.Atzmueller, M.: {Local Exceptionality Detection on Social Interaction Networks}. In: Proc. ECML-PKDD 2016: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Springer Verlag, Heidelberg, Germany (2016).
@inproceedings{Atzmueller:16,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin},
booktitle = {Proc. ECML-PKDD 2016: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
keywords = {interaction},
publisher = {Springer Verlag},
title = {{Local Exceptionality Detection on Social Interaction Networks}},
year = 2016
}%0 Conference Paper
%1 Atzmueller:16
%A Atzmueller, Martin
%B Proc. ECML-PKDD 2016: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
%C Heidelberg, Germany
%D 2016
%I Springer Verlag
%T {Local Exceptionality Detection on Social Interaction Networks}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-local-exceptionality-detection-ecml-pkdd-2016.pdf - 1.Atzmueller, M., Thiele, L., Stumme, G., Kauffeld, S.: {Analyzing Group Interaction and Dynamics on Socio-Behavioral Networks of Face-to-Face Proximity}. In: Proc. ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication. ACM Press, New York, NY, USA (2016).
@inproceedings{ATSK:16,
address = {New York, NY, USA},
author = {Atzmueller, Martin and Thiele, Lisa and Stumme, Gerd and Kauffeld, Simone},
booktitle = {Proc. ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication},
keywords = {behavior},
publisher = {ACM Press},
series = {UbiComp '16 Adjunct},
title = {{Analyzing Group Interaction and Dynamics on Socio-Behavioral Networks of Face-to-Face Proximity}},
year = 2016
}%0 Conference Paper
%1 ATSK:16
%A Atzmueller, Martin
%A Thiele, Lisa
%A Stumme, Gerd
%A Kauffeld, Simone
%B Proc. ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication
%C New York, NY, USA
%D 2016
%I ACM Press
%T {Analyzing Group Interaction and Dynamics on Socio-Behavioral Networks of Face-to-Face Proximity}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-analyzing-group-interaction-ubicomp16.pdf - 1.Atzmueller, M., Ernst, A., Krebs, F., Scholz, C., Stumme, G.: {Formation and Temporal Evolution of Social Groups During Coffee Breaks}. In: Postproceedings of the International Workshops MUSE & SenseML 2014, Nancy, France, and MSM 2014, Seoul, Korea. Springer Verlag, Heidelberg, Germany (2016).
@incollection{AEKSS:15,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin and Ernst, Andreas and Krebs, Friedrich and Scholz, Christoph and Stumme, Gerd},
booktitle = {Postproceedings of the International Workshops MUSE & SenseML 2014, Nancy, France, and MSM 2014, Seoul, Korea},
keywords = {group},
publisher = {Springer Verlag},
series = {LNAI},
title = {{Formation and Temporal Evolution of Social Groups During Coffee Breaks}},
year = 2016
}%0 Book Section
%1 AEKSS:15
%A Atzmueller, Martin
%A Ernst, Andreas
%A Krebs, Friedrich
%A Scholz, Christoph
%A Stumme, Gerd
%B Postproceedings of the International Workshops MUSE & SenseML 2014, Nancy, France, and MSM 2014, Seoul, Korea
%C Heidelberg, Germany
%D 2016
%I Springer Verlag
%T {Formation and Temporal Evolution of Social Groups During Coffee Breaks}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-atzmueller-group-formation-temporal-evolution.pdf - 1.Atzmueller, M.: {Community Detection: From Plain to Attributed Complex Networks}. In: Proc. ACM Web Science Conference. ACM Press, New York, NY, USA (2016).
@inproceedings{Atzmueller:16:websci,
address = {New York, NY, USA},
author = {Atzmueller, Martin},
booktitle = {Proc. ACM Web Science Conference},
keywords = 2016,
organization = {ACM},
publisher = {ACM Press},
title = {{Community Detection: From Plain to Attributed Complex Networks}},
year = 2016
}%0 Conference Paper
%1 Atzmueller:16:websci
%A Atzmueller, Martin
%B Proc. ACM Web Science Conference
%C New York, NY, USA
%D 2016
%I ACM Press
%T {Community Detection: From Plain to Attributed Complex Networks}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-atzmueller-websci-community-detection-on-complex-attributed-networks.pdf - 1.Atzmueller, M., Schmidt, A., Kloepper, B., Arnu, D.: {HypGraphs: An Approach for Modeling and Comparing Graph-Based and Sequential Hypotheses}. In: Proc. ECML-PKDD Workshop on New Frontiers in Mining Complex Patterns (NFMCP). , Riva del Garda, Italy (2016).
@inproceedings{ASKA:16,
address = {Riva del Garda, Italy},
author = {Atzmueller, Martin and Schmidt, Andreas and Kloepper, Benjamin and Arnu, David},
booktitle = {Proc. ECML-PKDD Workshop on New Frontiers in Mining Complex Patterns (NFMCP)},
keywords = {feepub},
title = {{HypGraphs: An Approach for Modeling and Comparing Graph-Based and Sequential Hypotheses}},
year = 2016
}%0 Conference Paper
%1 ASKA:16
%A Atzmueller, Martin
%A Schmidt, Andreas
%A Kloepper, Benjamin
%A Arnu, David
%B Proc. ECML-PKDD Workshop on New Frontiers in Mining Complex Patterns (NFMCP)
%C Riva del Garda, Italy
%D 2016
%T {HypGraphs: An Approach for Modeling and Comparing Graph-Based and Sequential Hypotheses}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2016-atzmueller-hypgraphs.pdf - 1.Atzmueller, M., Chin, A., Janssen, F., Schweizer, I., Trattner, C. eds.: {Big Data Analytics in the Social and Ubiquitous Context}. Springer Verlag, Heidelberg, Germany (2016).
@proceedings{ACJST:16,
address = {Heidelberg, Germany},
booktitle = {MSM/MUSE Postproceedings 2015},
editor = {Atzmueller, Martin and Chin, Alvin and Janssen, Frederik and Schweizer, Immanuel and Trattner, Christoph},
keywords = {big},
publisher = {Springer Verlag},
series = {Lecture Notes in Computer Science},
title = {{Big Data Analytics in the Social and Ubiquitous Context}},
volume = 9546,
year = 2016
}%0 Conference Proceedings
%1 ACJST:16
%B MSM/MUSE Postproceedings 2015
%C Heidelberg, Germany
%D 2016
%E Atzmueller, Martin
%E Chin, Alvin
%E Janssen, Frederik
%E Schweizer, Immanuel
%E Trattner, Christoph
%I Springer Verlag
%T {Big Data Analytics in the Social and Ubiquitous Context}
%V 9546 - 1.Lemmerich, F., Atzmueller, M., Puppe, F.: {Fast Exhaustive Subgroup Discovery with Numerical Target Concepts}. Data Mining and Knowledge Discovery. 30, 711–762 (2016).
@article{LAP:15,
author = {Lemmerich, Florian and Atzmueller, Martin and Puppe, Frank},
journal = {Data Mining and Knowledge Discovery},
keywords = {itegpub},
pages = {711-762},
title = {{Fast Exhaustive Subgroup Discovery with Numerical Target Concepts}},
volume = 30,
year = 2016
}%0 Journal Article
%1 LAP:15
%A Lemmerich, Florian
%A Atzmueller, Martin
%A Puppe, Frank
%D 2016
%J Data Mining and Knowledge Discovery
%P 711-762
%T {Fast Exhaustive Subgroup Discovery with Numerical Target Concepts}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-dmkd-preprint-sdnum.pdf
%V 30 - 1.Schmidt, A., Atzmueller, M., Hollender, M.: {Data Preparation for Big Data Analytics: Methods \& Experiences}. In: {Enterprise Big Data Engineering, Analytics, and Management}. IGI Global, Hershey, PA, USA (2016).
@incollection{ASH:16,
address = {Hershey, PA, USA},
author = {Schmidt, Andreas and Atzmueller, Martin and Hollender, Martin},
booktitle = {{Enterprise Big Data Engineering, Analytics, and Management}},
keywords = {big},
publisher = {IGI Global},
title = {{Data Preparation for Big Data Analytics: Methods \& Experiences}},
year = 2016
}%0 Book Section
%1 ASH:16
%A Schmidt, Andreas
%A Atzmueller, Martin
%A Hollender, Martin
%B {Enterprise Big Data Engineering, Analytics, and Management}
%C Hershey, PA, USA
%D 2016
%I IGI Global
%T {Data Preparation for Big Data Analytics: Methods \& Experiences}
%U http://www.igi-global.com/chapter/data-preparation-for-big-data-analytics/154561 - 1.Atzmueller, M., Kloepper, B., Mawla, H.A., Jäschke, B., Hollender, M., Graube, M., Arnu, D., Schmidt, A., Heinze, S., Schorer, L., Kroll, A., Stumme, G., Urbas, L.: {Big Data Analytics for Proactive Industrial Decision Support: Approaches \& First Experiences in the Context of the FEE Project}. atp edition. 58, (2016).
@article{FEE:ATP:2016,
author = {Atzmueller, Martin and Kloepper, Benjamin and Mawla, Hassan Al and Jäschke, Benjamin and Hollender, Martin and Graube, Markus and Arnu, David and Schmidt, Andreas and Heinze, Sebastian and Schorer, Lukas and Kroll, Andreas and Stumme, Gerd and Urbas, Leon},
journal = {atp edition},
keywords = {big},
number = 9,
title = {{Big Data Analytics for Proactive Industrial Decision Support: Approaches \& First Experiences in the Context of the FEE Project}},
volume = 58,
year = 2016
}%0 Journal Article
%1 FEE:ATP:2016
%A Atzmueller, Martin
%A Kloepper, Benjamin
%A Mawla, Hassan Al
%A Jäschke, Benjamin
%A Hollender, Martin
%A Graube, Markus
%A Arnu, David
%A Schmidt, Andreas
%A Heinze, Sebastian
%A Schorer, Lukas
%A Kroll, Andreas
%A Stumme, Gerd
%A Urbas, Leon
%D 2016
%J atp edition
%N 9
%T {Big Data Analytics for Proactive Industrial Decision Support: Approaches \& First Experiences in the Context of the FEE Project}
%U https://www.atpinfo.de/produkte/2016-big-data-analytics-for-proactive-industrial-decision-support/
%V 58 - 1.Atzmueller, M.: {Detecting Community Patterns Capturing Exceptional Link Trails}. In: Proc. IEEE/ACM ASONAM. IEEE Press, Boston, MA, USA (2016).
@inproceedings{Atzmueller:16:ASONAM,
address = {Boston, MA, USA},
author = {Atzmueller, Martin},
booktitle = {Proc. IEEE/ACM ASONAM},
keywords = {model},
publisher = {IEEE Press},
title = {{Detecting Community Patterns Capturing Exceptional Link Trails}},
year = 2016
}%0 Conference Paper
%1 Atzmueller:16:ASONAM
%A Atzmueller, Martin
%B Proc. IEEE/ACM ASONAM
%C Boston, MA, USA
%D 2016
%I IEEE Press
%T {Detecting Community Patterns Capturing Exceptional Link Trails}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-xtrails-asonam2016-preprint.pdf
2015
- 1.Doerfel, S., Jäschke, R., Stumme, G.: The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems. Transactions on Intelligent Systems and Technology. (2015).
@article{doerfel2015cores,
author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd},
journal = {Transactions on Intelligent Systems and Technology},
keywords = {benchmark},
publisher = {ACM},
title = {The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems},
year = 2015
}%0 Journal Article
%1 doerfel2015cores
%A Doerfel, Stephan
%A Jäschke, Robert
%A Stumme, Gerd
%D 2015
%I ACM
%J Transactions on Intelligent Systems and Technology
%T The Role of Cores in Recommender Benchmarking for Social Bookmarking Systems - 1.Dallmann, A., Lemmerich, F., Zoller, D., Hotho, A.: Media Bias in German Online Newspapers. In: 26th ACM Conference on Hypertext and Social Media. ACM, Cyprus, Turkey, September 1-4 (2015).
@inproceedings{dallmann2015media,
address = {Cyprus, Turkey, September 1-4},
author = {Dallmann, Alexander and Lemmerich, Florian and Zoller, Daniel and Hotho, Andreas},
booktitle = {26th ACM Conference on Hypertext and Social Media},
keywords = {bias},
publisher = {ACM},
title = {Media Bias in German Online Newspapers},
year = 2015
}%0 Conference Paper
%1 dallmann2015media
%A Dallmann, Alexander
%A Lemmerich, Florian
%A Zoller, Daniel
%A Hotho, Andreas
%B 26th ACM Conference on Hypertext and Social Media
%C Cyprus, Turkey, September 1-4
%D 2015
%I ACM
%T Media Bias in German Online Newspapers - 1.Kibanov, M., Atzmueller, M., Illig, J., Scholz, C., Barrat, A., Cattuto, C., Stumme, G.: Is Web Content a Good Proxy for Real-Life Interaction? A Case Study Considering Online and Offline Interactions of Computer Scientists. In: Proceedings of the 2015 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Paris, France, August 25-28, 2015 (2015).
@inproceedings{kibanov2015content,
author = {Kibanov, Mark and Atzmueller, Martin and Illig, Jens and Scholz, Christoph and Barrat, Alain and Cattuto, Ciro and Stumme, Gerd},
booktitle = {Proceedings of the 2015 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Paris, France, August 25-28, 2015},
keywords = {mark},
title = {Is Web Content a Good Proxy for Real-Life Interaction? A Case Study Considering Online and Offline Interactions of Computer Scientists},
year = 2015
}%0 Conference Paper
%1 kibanov2015content
%A Kibanov, Mark
%A Atzmueller, Martin
%A Illig, Jens
%A Scholz, Christoph
%A Barrat, Alain
%A Cattuto, Ciro
%A Stumme, Gerd
%B Proceedings of the 2015 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Paris, France, August 25-28, 2015
%D 2015
%T Is Web Content a Good Proxy for Real-Life Interaction? A Case Study Considering Online and Offline Interactions of Computer Scientists - 1.Zoller, D., Doerfel, S., Jäschke, R., Stumme, G., Hotho, A.: On Publication Usage in a Social Bookmarking System. In: Proceedings of the 2015 ACM Conference on Web Science. pp. 67:1–67:2. ACM, Oxford, United Kingdom (2015). https://doi.org/10.1145/2786451.2786927.Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.
@inproceedings{zoller2015publication,
abstract = {Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.},
address = {New York, NY, USA},
author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas},
booktitle = {Proceedings of the 2015 ACM Conference on Web Science},
keywords = {bookmarking},
pages = {67:1--67:2},
publisher = {ACM},
series = {WebSci '15},
title = {On Publication Usage in a Social Bookmarking System},
year = 2015
}%0 Conference Paper
%1 zoller2015publication
%A Zoller, Daniel
%A Doerfel, Stephan
%A Jäschke, Robert
%A Stumme, Gerd
%A Hotho, Andreas
%B Proceedings of the 2015 ACM Conference on Web Science
%C New York, NY, USA
%D 2015
%I ACM
%P 67:1--67:2
%R 10.1145/2786451.2786927
%T On Publication Usage in a Social Bookmarking System
%U http://doi.acm.org/10.1145/2786451.2786927
%X Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.
%@ 978-1-4503-3672-7 - 1.Kibanov, M.: Mining Groups Stability in Ubiquitous and Social Environments: Communities, Classes and Clusters. In: Cheng, X., Li, H., Gabrilovich, E., and Tang, J. (eds.) Proceedings of the Eighth ACM International Conference on Web Search and Data Mining. pp. 441–446. ACM, Shanghai, China (2015). https://doi.org/10.1145/2684822.2697034.Ubiquitous Computing is an emerging research area of computer science. Similarly, social network analysis and mining became very important in the last years. We aim to combine these two research areas to explore the nature of processes happening around users. The presented research focuses on exploring and analyzing different groups of persons or entities (communities, clusters and classes), their stability and semantics. An example of ubiquitous social data are social networks captured during scientific conferences using face-to-face RFID proximity tags. Another example of ubiquitous data is crowd-generated environmental sensor data. In this paper we generalize various problems connected to these and further datasets and consider them as a task for measuring group stability. Group stability can be used to improve state-of-the-art methods to analyze data. We also aim to improve the performance of different data mining algorithms, eg. by better handling of data with a skewed density distribution. We describe significant results some experiments that show how the presented approach can be applied and discuss the planned experiments.
@inproceedings{kibanov2015mining,
abstract = {Ubiquitous Computing is an emerging research area of computer science. Similarly, social network analysis and mining became very important in the last years. We aim to combine these two research areas to explore the nature of processes happening around users. The presented research focuses on exploring and analyzing different groups of persons or entities (communities, clusters and classes), their stability and semantics. An example of ubiquitous social data are social networks captured during scientific conferences using face-to-face RFID proximity tags. Another example of ubiquitous data is crowd-generated environmental sensor data. In this paper we generalize various problems connected to these and further datasets and consider them as a task for measuring group stability. Group stability can be used to improve state-of-the-art methods to analyze data. We also aim to improve the performance of different data mining algorithms, eg. by better handling of data with a skewed density distribution. We describe significant results some experiments that show how the presented approach can be applied and discuss the planned experiments.},
address = {New York, NY, USA},
author = {Kibanov, Mark},
booktitle = {Proceedings of the Eighth ACM International Conference on Web Search and Data Mining},
editor = {Cheng, Xueqi and Li, Hang and Gabrilovich, Evgeniy and Tang, Jie},
keywords = {itegpub},
pages = {441--446},
publisher = {ACM},
series = {WSDM '15},
title = {Mining Groups Stability in Ubiquitous and Social Environments: Communities, Classes and Clusters},
year = 2015
}%0 Conference Paper
%1 kibanov2015mining
%A Kibanov, Mark
%B Proceedings of the Eighth ACM International Conference on Web Search and Data Mining
%C New York, NY, USA
%D 2015
%E Cheng, Xueqi
%E Li, Hang
%E Gabrilovich, Evgeniy
%E Tang, Jie
%I ACM
%P 441--446
%R 10.1145/2684822.2697034
%T Mining Groups Stability in Ubiquitous and Social Environments: Communities, Classes and Clusters
%U http://doi.acm.org/10.1145/2684822.2697034
%X Ubiquitous Computing is an emerging research area of computer science. Similarly, social network analysis and mining became very important in the last years. We aim to combine these two research areas to explore the nature of processes happening around users. The presented research focuses on exploring and analyzing different groups of persons or entities (communities, clusters and classes), their stability and semantics. An example of ubiquitous social data are social networks captured during scientific conferences using face-to-face RFID proximity tags. Another example of ubiquitous data is crowd-generated environmental sensor data. In this paper we generalize various problems connected to these and further datasets and consider them as a task for measuring group stability. Group stability can be used to improve state-of-the-art methods to analyze data. We also aim to improve the performance of different data mining algorithms, eg. by better handling of data with a skewed density distribution. We describe significant results some experiments that show how the presented approach can be applied and discuss the planned experiments.
%@ 978-1-4503-3317-7 - 1.Tran, T., Tran, N.-K., Teka Hadgu, A., Jäschke, R.: Semantic Annotation for Microblog Topics Using Wikipedia Temporal Information. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics (2015).In this paper we study the problem of semantic annotation for a trending hashtag which is the crucial step towards analyzing user behavior in social media, yet has been largely unexplored. We tackle the problem via linking to entities from Wikipedia. We incorporate the social aspects of trending hashtags by identifying prominent entities for the annotation so as to maximize the information spreading in entity networks. We exploit temporal dynamics of entities in Wikipedia, namely Wikipedia edits and page views to improve the annotation quality. Our experiments show that we significantly outperform the established methods in tweet annotation.
@inproceedings{tran2015semantic,
abstract = {In this paper we study the problem of semantic annotation for a trending hashtag which is the crucial step towards analyzing user behavior in social media, yet has been largely unexplored. We tackle the problem via linking to entities from Wikipedia. We incorporate the social aspects of trending hashtags by identifying prominent entities for the annotation so as to maximize the information spreading in entity networks. We exploit temporal dynamics of entities in Wikipedia, namely Wikipedia edits and page views to improve the annotation quality. Our experiments show that we significantly outperform the established methods in tweet annotation.},
author = {Tran, Tuan and Tran, Nam-Khanh and Teka Hadgu, Asmelash and Jäschke, Robert},
booktitle = {Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
keywords = {temporal},
month = {09},
publisher = {Association for Computational Linguistics},
title = {Semantic Annotation for Microblog Topics Using Wikipedia Temporal Information},
year = 2015
}%0 Conference Paper
%1 tran2015semantic
%A Tran, Tuan
%A Tran, Nam-Khanh
%A Teka Hadgu, Asmelash
%A Jäschke, Robert
%B Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP)
%D 2015
%I Association for Computational Linguistics
%T Semantic Annotation for Microblog Topics Using Wikipedia Temporal Information
%X In this paper we study the problem of semantic annotation for a trending hashtag which is the crucial step towards analyzing user behavior in social media, yet has been largely unexplored. We tackle the problem via linking to entities from Wikipedia. We incorporate the social aspects of trending hashtags by identifying prominent entities for the annotation so as to maximize the information spreading in entity networks. We exploit temporal dynamics of entities in Wikipedia, namely Wikipedia edits and page views to improve the annotation quality. Our experiments show that we significantly outperform the established methods in tweet annotation. - 1.Sîrbu, A., Becker, M., Caminiti, S., De Baets, B., Elen, B., Francis, L., Gravino, P., Hotho, A., Ingarra, S., Loreto, V., Molino, A., Mueller, J., Peters, J., Ricchiuti, F., Saracino, F., Servedio, V.D.P., Stumme, G., Theunis, J., Tria, F., Van den Bossche, J.: Participatory Patterns in an International Air Quality Monitoring Initiative. PLOS ONE. 10, 1–19 (2015). https://doi.org/10.1371/journal.pone.0136763.The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.
@article{sirbu2015participatory,
abstract = {The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.},
author = {Sîrbu, Alina and Becker, Martin and Caminiti, Saverio and De Baets, Bernard and Elen, Bart and Francis, Louise and Gravino, Pietro and Hotho, Andreas and Ingarra, Stefano and Loreto, Vittorio and Molino, Andrea and Mueller, Juergen and Peters, Jan and Ricchiuti, Ferdinando and Saracino, Fabio and Servedio, Vito D. P. and Stumme, Gerd and Theunis, Jan and Tria, Francesca and Van den Bossche, Joris},
journal = {PLOS ONE},
keywords = {itegpub},
month = {08},
number = 8,
pages = {1-19},
publisher = {Public Library of Science},
title = {Participatory Patterns in an International Air Quality Monitoring Initiative},
volume = 10,
year = 2015
}%0 Journal Article
%1 sirbu2015participatory
%A Sîrbu, Alina
%A Becker, Martin
%A Caminiti, Saverio
%A De Baets, Bernard
%A Elen, Bart
%A Francis, Louise
%A Gravino, Pietro
%A Hotho, Andreas
%A Ingarra, Stefano
%A Loreto, Vittorio
%A Molino, Andrea
%A Mueller, Juergen
%A Peters, Jan
%A Ricchiuti, Ferdinando
%A Saracino, Fabio
%A Servedio, Vito D. P.
%A Stumme, Gerd
%A Theunis, Jan
%A Tria, Francesca
%A Van den Bossche, Joris
%D 2015
%I Public Library of Science
%J PLOS ONE
%N 8
%P 1-19
%R 10.1371/journal.pone.0136763
%T Participatory Patterns in an International Air Quality Monitoring Initiative
%U https://doi.org/10.1371/journal.pone.0136763
%V 10
%X The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution. - 1.Atzmueller, M., Chin, A., Scholz, C., Trattner, C. eds.: {Mining, Modeling and Recommending ’Things’ in Social Media}. Springer Verlag, Heidelberg, Germany (2015).
@book{ACST:15,
address = {Heidelberg, Germany},
booktitle = {MSM/MUSE Postproceedings 2013},
editor = {Atzmueller, Martin and Chin, Alvin and Scholz, Christoph and Trattner, Christoph},
journal = {LNCS},
keywords = {itegpub},
publisher = {Springer Verlag},
series = {LNCS},
title = {{Mining, Modeling and Recommending 'Things' in Social Media}},
volume = 8940,
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}%0 Book
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%E Atzmueller, Martin
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%E Scholz, Christoph
%E Trattner, Christoph
%I Springer Verlag
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%T {Mining, Modeling and Recommending 'Things' in Social Media}
%V 8940
%@ 978-3-642-23598-6 - 1.Atzmueller, M., Mueller, J., Becker, M.: {Exploratory Subgroup Analytics on Ubiquitous Data}. In: Mining, Modeling and Recommending ’Things’ in Social Media. Springer Verlag, Heidelberg, Germany (2015).
@incollection{AMB:15,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin and Mueller, Juergen and Becker, Martin},
booktitle = {Mining, Modeling and Recommending 'Things' in Social Media},
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publisher = {Springer Verlag},
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title = {{Exploratory Subgroup Analytics on Ubiquitous Data}},
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}%0 Book Section
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%B Mining, Modeling and Recommending 'Things' in Social Media
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%I Springer Verlag
%T {Exploratory Subgroup Analytics on Ubiquitous Data}
%V 8940 - 1.Singer, P., Helic, D., Hotho, A., Strohmaier, M.: Hyptrails: A bayesian approach for comparing hypotheses about human trails. In: 24th International World Wide Web Conference (WWW2015). ACM, Firenze, Italy (2015).
@inproceedings{singer2015hyptrails,
address = {Firenze, Italy},
author = {Singer, P. and Helic, D. and Hotho, A. and Strohmaier, M.},
booktitle = {24th International World Wide Web Conference (WWW2015)},
keywords = {bibsonomy},
month = {05},
organization = {ACM},
publisher = {ACM},
title = {Hyptrails: A bayesian approach for comparing hypotheses about human trails},
year = 2015
}%0 Conference Paper
%1 singer2015hyptrails
%A Singer, P.
%A Helic, D.
%A Hotho, A.
%A Strohmaier, M.
%B 24th International World Wide Web Conference (WWW2015)
%C Firenze, Italy
%D 2015
%I ACM
%T Hyptrails: A bayesian approach for comparing hypotheses about human trails
%U http://www.www2015.it/documents/proceedings/proceedings/p1003.pdf - 1.Atzmueller, M.: {Subgroup and Community Analytics on Attributed Graphs}. In: Proc. International Workshop on Social Network Analysis using Formal Concept Analysis (SNAFCA-2015). CEUR-WS (2015).
@inproceedings{Atzmueller:15b,
author = {Atzmueller, Martin},
booktitle = {Proc. International Workshop on Social Network Analysis using Formal Concept Analysis (SNAFCA-2015)},
keywords = 2015,
publisher = {CEUR-WS},
title = {{Subgroup and Community Analytics on Attributed Graphs}},
year = 2015
}%0 Conference Paper
%1 Atzmueller:15b
%A Atzmueller, Martin
%B Proc. International Workshop on Social Network Analysis using Formal Concept Analysis (SNAFCA-2015)
%D 2015
%I CEUR-WS
%T {Subgroup and Community Analytics on Attributed Graphs}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-atzmueller-snafca-community-analytics.pdf - 1.Atzmueller, M., Doerfel, S., Mitzlaff, F.: {Fast Description-Oriented Community Detection using Subgroup Discovery (Extended Abstract, Resubmission)}. In: Proc. LWA 2015 (KDML Special Track) (2015).
@inproceedings{ADM:15b,
author = {Atzmueller, Martin and Doerfel, Stephan and Mitzlaff, Folke},
booktitle = {Proc. LWA 2015 (KDML Special Track)},
keywords = 2015,
title = {{Fast Description-Oriented Community Detection using Subgroup Discovery (Extended Abstract, Resubmission)}},
year = 2015
}%0 Conference Paper
%1 ADM:15b
%A Atzmueller, Martin
%A Doerfel, Stephan
%A Mitzlaff, Folke
%B Proc. LWA 2015 (KDML Special Track)
%D 2015
%T {Fast Description-Oriented Community Detection using Subgroup Discovery (Extended Abstract, Resubmission)}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-lwa-kdml-atzmueller.pdf - 1.Knoell, D., Rieder, C., Atzmueller, M., Scherer, K.P.: {Towards Generating Test Ontologies using Subgroup Discovery}. In: Proc. LWA 2015 (WM Special Track) (2015).
@inproceedings{KRAS:15,
author = {Knoell, Daniel and Rieder, Constantin and Atzmueller, Martin and Scherer, Klaus Peter},
booktitle = {Proc. LWA 2015 (WM Special Track)},
keywords = {ontology},
title = {{Towards Generating Test Ontologies using Subgroup Discovery}},
year = 2015
}%0 Conference Paper
%1 KRAS:15
%A Knoell, Daniel
%A Rieder, Constantin
%A Atzmueller, Martin
%A Scherer, Klaus Peter
%B Proc. LWA 2015 (WM Special Track)
%D 2015
%T {Towards Generating Test Ontologies using Subgroup Discovery}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-lwa-kdml-sd-ontology-testing.pdf - 1.Schmidt, A., Atzmueller, M., Stumme, G.: The FEE Project: Introduction and First Insights. In: Proc. UIS Workshop (2015).
@inproceedings{schmidt2015project,
author = {Schmidt, Andreas and Atzmueller, Martin and Stumme, Gerd},
booktitle = {Proc. UIS Workshop},
keywords = {myown},
title = {The FEE Project: Introduction and First Insights},
year = 2015
}%0 Conference Paper
%1 schmidt2015project
%A Schmidt, Andreas
%A Atzmueller, Martin
%A Stumme, Gerd
%B Proc. UIS Workshop
%D 2015
%T The FEE Project: Introduction and First Insights
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-uis-big-data-fee-first-insights.pdf - 1.Atzmueller, M., Kibanov, M., Scholz, C., Mueller, J., Stumme, G.: {Conferator – A Ubiquitous System for Enhancing Social Networking at Conferences}. In: Proc. UIS Workshop (2015).
@inproceedings{atzmueller2015conferator,
author = {Atzmueller, Martin and Kibanov, Mark and Scholz, Christoph and Mueller, Juergen and Stumme, Gerd},
booktitle = {Proc. UIS Workshop},
keywords = {myown},
title = {{Conferator – A Ubiquitous System for Enhancing Social Networking at Conferences}},
year = 2015
}%0 Conference Paper
%1 atzmueller2015conferator
%A Atzmueller, Martin
%A Kibanov, Mark
%A Scholz, Christoph
%A Mueller, Juergen
%A Stumme, Gerd
%B Proc. UIS Workshop
%D 2015
%T {Conferator – A Ubiquitous System for Enhancing Social Networking at Conferences}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-uis-atzmueller-conferator-ubiquitous-social-computing.pdf - 1.v. Kistowski, J., Nikolas, H., Zoller, D., Kounev, S., Hotho, A.: Modeling and Extracting Load Intensity Profiles. In: Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) (2015).Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.
@inproceedings{vkistowski2015modeling,
abstract = {Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.},
author = {v. Kistowski, Jóakim and Nikolas, Herbst. and Zoller, Daniel and Kounev, Samuel and Hotho, Andreas},
booktitle = {Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)},
keywords = {extracting},
title = {Modeling and Extracting Load Intensity Profiles},
year = 2015
}%0 Conference Paper
%1 vkistowski2015modeling
%A v. Kistowski, Jóakim
%A Nikolas, Herbst.
%A Zoller, Daniel
%A Kounev, Samuel
%A Hotho, Andreas
%B Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)
%D 2015
%T Modeling and Extracting Load Intensity Profiles
%X Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches. - 1.Ring, M., Otto, F., Becker, M., Niebler, T., Landes, D., Hotho, A.: ConDist: A Context-Driven Categorical Distance Measure. Presented at the (2015).
@inproceedings{ring2015condist,
author = {Ring, Markus and Otto, Florian and Becker, Martin and Niebler, Thomas and Landes, Dieter and Hotho, Andreas},
editor = {ECMLPKDD2015},
keywords = {categorical},
title = {ConDist: A Context-Driven Categorical Distance Measure},
year = 2015
}%0 Conference Paper
%1 ring2015condist
%A Ring, Markus
%A Otto, Florian
%A Becker, Martin
%A Niebler, Thomas
%A Landes, Dieter
%A Hotho, Andreas
%D 2015
%E ECMLPKDD2015,
%T ConDist: A Context-Driven Categorical Distance Measure - 1.Pujari, S.C., Teka Hadgu, A., Lex, E., Jäschke, R.: Social Activity versus Academic Activity: A Case Study of Computer Scientists on Twitter. In: Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business. ACM, New York, NY, USA (2015). https://doi.org/10.1145/2809563.2809584.In this work, we study social and academic network activities of researchers from Computer Science. Using a recently proposed framework, we map the researchers to their Twitter accounts and link them to their publications. This enables us to create two types of networks: first, networks that reflect social activities on Twitter, namely the researchers’ follow, retweet and mention networks and second, networks that reflect academic activities, that is the co-authorship and citation networks. Based on these datasets, we (i) compare the social activities of researchers with their academic activities, (ii) investigate the consistency and similarity of communities within the social and academic activity networks, and (iii) investigate the information flow between different areas of Computer Science in and between both types of networks. Our findings show that if co-authors interact on Twitter, their relationship is reciprocal, increasing with the numbers of papers they co-authored. In general, the social and the academic activities are not correlated. In terms of community analysis, we found that the three social activity networks are most consistent with each other, with the highest consistency between the retweet and mention network. A study of information flow revealed that in the follow network, researchers from Data Management, Human-Computer Interaction, and Artificial Intelligence act as a source of information for other areas in Computer Science.
@inproceedings{pujari2015social,
abstract = {In this work, we study social and academic network activities of researchers from Computer Science. Using a recently proposed framework, we map the researchers to their Twitter accounts and link them to their publications. This enables us to create two types of networks: first, networks that reflect social activities on Twitter, namely the researchers’ follow, retweet and mention networks and second, networks that reflect academic activities, that is the co-authorship and citation networks. Based on these datasets, we (i) compare the social activities of researchers with their academic activities, (ii) investigate the consistency and similarity of communities within the social and academic activity networks, and (iii) investigate the information flow between different areas of Computer Science in and between both types of networks. Our findings show that if co-authors interact on Twitter, their relationship is reciprocal, increasing with the numbers of papers they co-authored. In general, the social and the academic activities are not correlated. In terms of community analysis, we found that the three social activity networks are most consistent with each other, with the highest consistency between the retweet and mention network. A study of information flow revealed that in the follow network, researchers from Data Management, Human-Computer Interaction, and Artificial Intelligence act as a source of information for other areas in Computer Science.},
address = {New York, NY, USA},
author = {Pujari, Subhash Chandra and Teka Hadgu, Asmelash and Lex, Elisabeth and Jäschke, Robert},
booktitle = {Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business},
keywords = {network},
publisher = {ACM},
series = {i-KNOW '15},
title = {Social Activity versus Academic Activity: A Case Study of Computer Scientists on Twitter},
year = 2015
}%0 Conference Paper
%1 pujari2015social
%A Pujari, Subhash Chandra
%A Teka Hadgu, Asmelash
%A Lex, Elisabeth
%A Jäschke, Robert
%B Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business
%C New York, NY, USA
%D 2015
%I ACM
%R 10.1145/2809563.2809584
%T Social Activity versus Academic Activity: A Case Study of Computer Scientists on Twitter
%U http://dx.doi.org/10.1145/2809563.2809584
%X In this work, we study social and academic network activities of researchers from Computer Science. Using a recently proposed framework, we map the researchers to their Twitter accounts and link them to their publications. This enables us to create two types of networks: first, networks that reflect social activities on Twitter, namely the researchers’ follow, retweet and mention networks and second, networks that reflect academic activities, that is the co-authorship and citation networks. Based on these datasets, we (i) compare the social activities of researchers with their academic activities, (ii) investigate the consistency and similarity of communities within the social and academic activity networks, and (iii) investigate the information flow between different areas of Computer Science in and between both types of networks. Our findings show that if co-authors interact on Twitter, their relationship is reciprocal, increasing with the numbers of papers they co-authored. In general, the social and the academic activities are not correlated. In terms of community analysis, we found that the three social activity networks are most consistent with each other, with the highest consistency between the retweet and mention network. A study of information flow revealed that in the follow network, researchers from Data Management, Human-Computer Interaction, and Artificial Intelligence act as a source of information for other areas in Computer Science. - 1.Atzmueller, M.: {Subgroup Discovery - Advanced Review}. WIREs: Data Mining and Knowledge Discovery. 5, 35–49 (2015). https://doi.org/10.1002/widm.1144.Subgroup discovery is a broadly applicable descriptive data mining technique for identifying interesting subgroups according to some property of interest. This article summarizes fundamentals of subgroup discovery, before it reviews algorithms and further advanced methodological issues. In addition, we briefly discuss tools and applications of subgroup discovery approaches. In that context, we also discuss experiences and lessons learned and outline future directions in order to show the advantages and benefits of subgroup discovery.
@article{Atzmueller:15a,
abstract = {Subgroup discovery is a broadly applicable descriptive data mining technique for identifying interesting subgroups according to some property of interest. This article summarizes fundamentals of subgroup discovery, before it reviews algorithms and further advanced methodological issues. In addition, we briefly discuss tools and applications of subgroup discovery approaches. In that context, we also discuss experiences and lessons learned and outline future directions in order to show the advantages and benefits of subgroup discovery.},
author = {Atzmueller, Martin},
journal = {WIREs: Data Mining and Knowledge Discovery},
keywords = {itegpub},
number = 1,
pages = {35--49},
title = {{Subgroup Discovery - Advanced Review}},
volume = 5,
year = 2015
}%0 Journal Article
%1 Atzmueller:15a
%A Atzmueller, Martin
%D 2015
%J WIREs: Data Mining and Knowledge Discovery
%N 1
%P 35--49
%R 10.1002/widm.1144
%T {Subgroup Discovery - Advanced Review}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-subgroup-discovery-advanced-review-wires-2015.pdf
%V 5
%X Subgroup discovery is a broadly applicable descriptive data mining technique for identifying interesting subgroups according to some property of interest. This article summarizes fundamentals of subgroup discovery, before it reviews algorithms and further advanced methodological issues. In addition, we briefly discuss tools and applications of subgroup discovery approaches. In that context, we also discuss experiences and lessons learned and outline future directions in order to show the advantages and benefits of subgroup discovery. - 1.Atzmueller, M.: {Subgroup and Community Analytics}, https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-atzmueller-cssws15-abstract.pdf, (2015).
@misc{Atzmueller:15:CSSWS,
author = {Atzmueller, Martin},
editor = {Symposium, Computational Social Science Winter},
howpublished = {Tutorial Abstract},
keywords = {community},
title = {{Subgroup and Community Analytics}},
year = 2015
}%0 Generic
%1 Atzmueller:15:CSSWS
%A Atzmueller, Martin
%D 2015
%E Symposium, Computational Social Science Winter
%T {Subgroup and Community Analytics}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-atzmueller-cssws15-abstract.pdf - 1.Kibanov, M., Amin, I., Lee, J.G.: Supporting Peat Fire Management using Social Media, (2015).Peat fires and haze originating from such fires cause a large spectrum of ecological, social and economical problems as well as health issues. Indonesia is a country where peat fires are prevalent and the population suffers from the ensuing haze problems. Two Indonesian islands (Sumatra and Kalimantan) are most affected by peat fires. In this abstract, considering the fact that the usage of social media in Indonesia is high (with 72 million accounts in social networks), it is expected that insights generated from social media can help central and local authorities to improve peat fire management. In particular, we focus on peat fires in the year 2014 in Riau Province, which is one of the most haze-affected areas on Sumatra Island.
@misc{kibanov2015supporting,
abstract = {Peat fires and haze originating from such fires cause a large spectrum of ecological, social and economical problems as well as health issues. Indonesia is a country where peat fires are prevalent and the population suffers from the ensuing haze problems. Two Indonesian islands (Sumatra and Kalimantan) are most affected by peat fires. In this abstract, considering the fact that the usage of social media in Indonesia is high (with 72 million accounts in social networks), it is expected that insights generated from social media can help central and local authorities to improve peat fire management. In particular, we focus on peat fires in the year 2014 in Riau Province, which is one of the most haze-affected areas on Sumatra Island.},
author = {Kibanov, Mark and Amin, Imaduddin and Lee, Jong Gun},
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%U http://www.gesis.org/css-wintersymposium/program/poster-sessions-presentations/ - 1.Atzmueller, M.: {Subgroup Discovery and Community Detection on Attributed Graphs}, https://www.kde.cs.uni-kassel.de/atzmueller/paper/2015-atzmueller-asonam15-abstract.pdf, (2015).
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@inproceedings{AKHTK:15,
address = {Porto, Portugal},
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2014
- 1.Scholz, C., Macek, B.-E., Atzmueller, M., Doerfel, S., Stumme, G.: {Socio-technical Design of Ubiquitous Computing Systems}. Presented at the , Heidelberg, Germany (2014).
@incollection{scholz2014sociotechnical,
address = {Heidelberg, Germany},
author = {Scholz, Christoph and Macek, Bjoern-Elmar and Atzmueller, Martin and Doerfel, Stephan and Stumme, Gerd},
chapter = {{Mining Social Links for Ubiquitous Knowledge Engineering}},
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%& {Mining Social Links for Ubiquitous Knowledge Engineering} - 1.Mitzlaff, F., Doerfel, S., Hotho, A., Jäschke, R., Mueller, J.: Summary of the 15th Discovery Challenge: Recommending Given Names. In: 15th Discovery Challenge of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013, Prague, Czech Republic - Sctober 27, 2013. Proceedings. pp. 7–24. CEUR-WS, Aachen, Germany (2014).The 15th ECML PKDD Discovery Challenge centered around the recommendation of given names. Participants of the challenge implemented algorithms that were tested both offline - on data collected by the name search engine Nameling - and online within Nameling. Here, we describe both tasks in detail and discuss the publicly available datasets. We motivate and explain the chosen evaluation of the challenge, and we summarize the different approaches applied to the name recommendation tasks. Finally, we present the rankings and winners of the offline and the online phase.
@inproceedings{mueller-2014a,
abstract = {The 15th ECML PKDD Discovery Challenge centered around the recommendation of given names. Participants of the challenge implemented algorithms that were tested both offline - on data collected by the name search engine Nameling - and online within Nameling. Here, we describe both tasks in detail and discuss the publicly available datasets. We motivate and explain the chosen evaluation of the challenge, and we summarize the different approaches applied to the name recommendation tasks. Finally, we present the rankings and winners of the offline and the online phase.},
address = {Aachen, Germany},
author = {Mitzlaff, Folke and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Mueller, Juergen},
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%X The 15th ECML PKDD Discovery Challenge centered around the recommendation of given names. Participants of the challenge implemented algorithms that were tested both offline - on data collected by the name search engine Nameling - and online within Nameling. Here, we describe both tasks in detail and discuss the publicly available datasets. We motivate and explain the chosen evaluation of the challenge, and we summarize the different approaches applied to the name recommendation tasks. Finally, we present the rankings and winners of the offline and the online phase. - 1.Cantador, I., Chi, M., Farzan, R., Jäschke, R. eds.: UMAP 2014 Extended Proceedings. CEUR-WS (2014).The workshops at the 22nd conference on User Modeling, Adaptation and Personalization cover broad and exciting topics related to ongoing research in the field. The workshops bring together researchers from a large number of academic institutions across the United States and Europe. Forty three papers at six workshops at UMAP 2014 highlight the impact of different factors such as human factors and emotions on user modeling. At the same time, the workshops attempt to discuss new challenges in the field such as news recommendation in the age of social media, student modeling in the context of MOOCs and gamified learning environments, and personalization in citizen-participatory e-government services and multilingual information systems.
@proceedings{cantador2014umap,
abstract = {The workshops at the 22nd conference on User Modeling, Adaptation and Personalization cover broad and exciting topics related to ongoing research in the field. The workshops bring together researchers from a large number of academic institutions across the United States and Europe. Forty three papers at six workshops at UMAP 2014 highlight the impact of different factors such as human factors and emotions on user modeling. At the same time, the workshops attempt to discuss new challenges in the field such as news recommendation in the age of social media, student modeling in the context of MOOCs and gamified learning environments, and personalization in citizen-participatory e-government services and multilingual information systems.},
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%X The workshops at the 22nd conference on User Modeling, Adaptation and Personalization cover broad and exciting topics related to ongoing research in the field. The workshops bring together researchers from a large number of academic institutions across the United States and Europe. Forty three papers at six workshops at UMAP 2014 highlight the impact of different factors such as human factors and emotions on user modeling. At the same time, the workshops attempt to discuss new challenges in the field such as news recommendation in the age of social media, student modeling in the context of MOOCs and gamified learning environments, and personalization in citizen-participatory e-government services and multilingual information systems. - 1.Hernandez, N., Jäschke, R., Croitoru, M. eds.: Graph-Based Representation and Reasoning. Springer (2014).This book constitutes the proceedings of the 21st International Conference on Conceptual Structures, ICCS 2014, held in Iaşi, Romania, in July 2014. The 17 regular papers and 6 short papers presented in this volume were carefully reviewed and selected from 40 and 10 submissions, respectively. The topics covered are: conceptual structures, knowledge representation, reasoning, conceptual graphs, formal concept analysis, semantic Web, information integration, machine learning, data mining and information retrieval.
@proceedings{hernandez2014graphbased,
abstract = {This book constitutes the proceedings of the 21st International Conference on Conceptual Structures, ICCS 2014, held in Iaşi, Romania, in July 2014. The 17 regular papers and 6 short papers presented in this volume were carefully reviewed and selected from 40 and 10 submissions, respectively. The topics covered are: conceptual structures, knowledge representation, reasoning, conceptual graphs, formal concept analysis, semantic Web, information integration, machine learning, data mining and information retrieval.},
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%@ 978-3-319-08388-9 - 1.Scholz, C., Illig, J., Atzmueller, M., Stumme, G.: {On the Predictability of Talk Attendance at Academic Conferences (Extended Version)}. CoRR. abs/1407.0613, (2014).
@article{SIAS:14c,
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%V abs/1407.0613 - 1.Blümel, I., Dietze, S., Heller, L., Jäschke, R., Mehlberg, M.: The Quest for Research Information. In: Proceedings of the 12th International Conference on Current Research Information Systems. euroCRIS (2014).Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing on institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, the limited amounts of structured data often are exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic view on research information across organisational and national boundaries is not feasible and information is inconsistent and incomplete. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In particular the Linked Data community has provided a range of techniques, schemas and vocabularies which allow to represent and interlink research information in a more coherent manner. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources.
@inproceedings{bluemel2014quest,
abstract = {Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing on institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, the limited amounts of structured data often are exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic view on research information across organisational and national boundaries is not feasible and information is inconsistent and incomplete. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In particular the Linked Data community has provided a range of techniques, schemas and vocabularies which allow to represent and interlink research information in a more coherent manner. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources.},
author = {Blümel, Ina and Dietze, Stefan and Heller, Lambert and Jäschke, Robert and Mehlberg, Martin},
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%X Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing on institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, the limited amounts of structured data often are exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic view on research information across organisational and national boundaries is not feasible and information is inconsistent and incomplete. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In particular the Linked Data community has provided a range of techniques, schemas and vocabularies which allow to represent and interlink research information in a more coherent manner. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources. - 1.Illig, J., Roth, B., Klakow, D.: Unsupervised Parsing for Generating Surface-Based Relation Extraction Patterns. In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers. pp. 100–105. Association for Computational Linguistics, Gothenburg, Sweden (2014).Finding the right features and patterns for identifying relations in natural language is one of the most pressing research questions for relation extraction. In this paper, we compare patterns based on supervised and unsupervised syntactic parsing and present a simple method for extracting surface patterns from a parsed training set. Results show that the use of surface-based patterns not only increases extraction speed, but also improves the quality of the extracted relations. We find that, in this setting, unsupervised parsing, besides requiring less resources, compares favorably in terms of extraction quality.
@inproceedings{illig-roth-klakow:2014:EACL2014-SP,
abstract = {Finding the right features and patterns for identifying relations in natural language is one of the most pressing research questions for relation extraction. In this paper, we compare patterns based on supervised and unsupervised syntactic parsing and present a simple method for extracting surface patterns from a parsed training set. Results show that the use of surface-based patterns not only increases extraction speed, but also improves the quality of the extracted relations. We find that, in this setting, unsupervised parsing, besides requiring less resources, compares favorably in terms of extraction quality.},
address = {Gothenburg, Sweden},
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@article{mueller-2014b,
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@article{KASS:14,
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%V 57 - 1.Doerfel, S., Hotho, A., Jäschke, R., Mitzlaff, F., Mueller, J. eds.: Proceedings of the ECML PKDD Discovery Challenge 2013 - Recommending Given Names. (2014).
@proceedings{doerfel2014discovery,
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%V 1120 - 1.Atzmueller, M., Baraki, H., Behrenbruch, K., Comes, D., Evers, C., Hoffmann, A., Hoffmann, H., Jandt, S., Kibanov, M., Kieselmann, O., Kniewel, R., König, I., Macek, B.-E., Niemczyk, S., Scholz, C., Schuldt, M., Schulz, T., Skistims, H., Söllner, M., Voigtmann, C., Witsch, A., Zirfas, J.: {Die VENUS-Entwicklungsmethode: Eine interdisziplinäre Methode für soziotechnische Softwaregestaltung}. Research Center for Information System Design (ITeG), University of Kassel (2014).
@techreport{Atzmueller:VENUSEntwicklungsmethode:2014,
author = {Atzmueller, Martin and Baraki, Harun and Behrenbruch, Kay and Comes, Diana and Evers, Christoph and Hoffmann, Axel and Hoffmann, Holger and Jandt, Silke and Kibanov, Mark and Kieselmann, Olga and Kniewel, Romy and König, Immanuel and Macek, Björn-Elmar and Niemczyk, Stefan and Scholz, Christoph and Schuldt, Michaela and Schulz, Thomas and Skistims, Hendrik and Söllner, Matthias and Voigtmann, Christian and Witsch, Andreas and Zirfas, Julia},
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%A Behrenbruch, Kay
%A Comes, Diana
%A Evers, Christoph
%A Hoffmann, Axel
%A Hoffmann, Holger
%A Jandt, Silke
%A Kibanov, Mark
%A Kieselmann, Olga
%A Kniewel, Romy
%A König, Immanuel
%A Macek, Björn-Elmar
%A Niemczyk, Stefan
%A Scholz, Christoph
%A Schuldt, Michaela
%A Schulz, Thomas
%A Skistims, Hendrik
%A Söllner, Matthias
%A Voigtmann, Christian
%A Witsch, Andreas
%A Zirfas, Julia
%D 2014
%E Hoffmann, Axel
%E Niemczyk, Stefan
%T {Die VENUS-Entwicklungsmethode: Eine interdisziplinäre Methode für soziotechnische Softwaregestaltung} - 1.Atzmueller, M.: {Data Mining on Social Interaction Networks}. Journal of Data Mining and Digital Humanities. 1, (2014).
@article{Atzmueller:14:CoRR,
author = {Atzmueller, Martin},
journal = {Journal of Data Mining and Digital Humanities},
keywords = {conferator},
month = {06},
title = {{Data Mining on Social Interaction Networks}},
volume = 1,
year = 2014
}%0 Journal Article
%1 Atzmueller:14:CoRR
%A Atzmueller, Martin
%D 2014
%J Journal of Data Mining and Digital Humanities
%T {Data Mining on Social Interaction Networks}
%U https://jdmdh.episciences.org/11/pdf
%V 1 - 1.Macek, B.-E., Atzmueller, M., Stumme, G.: {Predicting the Stability of User Interaction Ties in Twitter}. In: Proc. I-KNOW 2014. ACM Press, New York, NY, USA (2014).
@inproceedings{MAS:14,
address = {New York, NY, USA},
author = {Macek, Bjoern-Elmar and Atzmueller, Martin and Stumme, Gerd},
booktitle = {Proc. I-KNOW 2014},
keywords = {analysis},
publisher = {ACM Press},
title = {{Predicting the Stability of User Interaction Ties in Twitter}},
year = 2014
}%0 Conference Paper
%1 MAS:14
%A Macek, Bjoern-Elmar
%A Atzmueller, Martin
%A Stumme, Gerd
%B Proc. I-KNOW 2014
%C New York, NY, USA
%D 2014
%I ACM Press
%T {Predicting the Stability of User Interaction Ties in Twitter} - 1.Becker, M., Hotho, A., Mueller, J., Kibanov, M., Atzmueller, M., Stumme, G.: Subjective vs. Objective Data: Bridging the Gap, http://www.gesis.org/en/events/css-wintersymposium/poster-presentation/, (2014).Sensor data is objective. But when measuring our environment, measured values are contrasted with our perception, which is always subjective. This makes interpreting sensor measurements difficult for a single person in her personal environment. In this context, the EveryAware projects directly connects the concepts of objective sensor data with subjective impressions and perceptions by providing a collective sensing platform with several client applications allowing to explicitly associate those two data types. The goal is to provide the user with personalized feedback, a characterization of the global as well as her personal environment, and enable her to position her perceptions in this global context. In this poster we summarize the collected data of two EveryAware applications, namely WideNoise for noise measurements and AirProbe for participatory air quality sensing. Basic insights are presented including user activity, learning processes and sensor data to perception correlations. These results provide an outlook on how this data can further be used to understand the connection between sensor data and perceptions.
@misc{becker2014subjective,
abstract = {Sensor data is objective. But when measuring our environment, measured values are contrasted with our perception, which is always subjective. This makes interpreting sensor measurements difficult for a single person in her personal environment. In this context, the EveryAware projects directly connects the concepts of objective sensor data with subjective impressions and perceptions by providing a collective sensing platform with several client applications allowing to explicitly associate those two data types. The goal is to provide the user with personalized feedback, a characterization of the global as well as her personal environment, and enable her to position her perceptions in this global context. In this poster we summarize the collected data of two EveryAware applications, namely WideNoise for noise measurements and AirProbe for participatory air quality sensing. Basic insights are presented including user activity, learning processes and sensor data to perception correlations. These results provide an outlook on how this data can further be used to understand the connection between sensor data and perceptions.},
author = {Becker, Martin and Hotho, Andreas and Mueller, Juergen and Kibanov, Mark and Atzmueller, Martin and Stumme, Gerd},
howpublished = {CSSWS 2014, Poster},
keywords = {everyaware},
title = {Subjective vs. Objective Data: Bridging the Gap},
year = 2014
}%0 Generic
%1 becker2014subjective
%A Becker, Martin
%A Hotho, Andreas
%A Mueller, Juergen
%A Kibanov, Mark
%A Atzmueller, Martin
%A Stumme, Gerd
%D 2014
%T Subjective vs. Objective Data: Bridging the Gap
%U http://www.gesis.org/en/events/css-wintersymposium/poster-presentation/
%X Sensor data is objective. But when measuring our environment, measured values are contrasted with our perception, which is always subjective. This makes interpreting sensor measurements difficult for a single person in her personal environment. In this context, the EveryAware projects directly connects the concepts of objective sensor data with subjective impressions and perceptions by providing a collective sensing platform with several client applications allowing to explicitly associate those two data types. The goal is to provide the user with personalized feedback, a characterization of the global as well as her personal environment, and enable her to position her perceptions in this global context. In this poster we summarize the collected data of two EveryAware applications, namely WideNoise for noise measurements and AirProbe for participatory air quality sensing. Basic insights are presented including user activity, learning processes and sensor data to perception correlations. These results provide an outlook on how this data can further be used to understand the connection between sensor data and perceptions. - 1.Atzmueller, M., Behrenbruch, K., Hoffmann, A., Kibanov, M., Macek, B.-E., Scholz, C., Skistims, H., Söllner, M., Stumme, G.: {Connect-U: A System for Enhancing Social Networking}. In: David, K., Geihs, K., Leimeister, J.-M., Roßnagel, A., Schmidt, L., Stumme, G., and Wacker, A. (eds.) {Socio-technical Design of Ubiquitous Computing Systems}. Springer Verlag, Heidelberg, Germany (2014).
@incollection{ABHKMSSSS:14,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin and Behrenbruch, Kay and Hoffmann, Axel and Kibanov, Mark and Macek, Bjoern-Elmar and Scholz, Christoph and Skistims, Hendrik and Söllner, Matthias and Stumme, Gerd},
booktitle = {{Socio-technical Design of Ubiquitous Computing Systems}},
editor = {David, Klaus and Geihs, Kurt and Leimeister, Jan-Marco and Roßnagel, Alexander and Schmidt, Ludger and Stumme, Gerd and Wacker, Arno},
keywords = {network},
publisher = {Springer Verlag},
title = {{Connect-U: A System for Enhancing Social Networking}},
year = 2014
}%0 Book Section
%1 ABHKMSSSS:14
%A Atzmueller, Martin
%A Behrenbruch, Kay
%A Hoffmann, Axel
%A Kibanov, Mark
%A Macek, Bjoern-Elmar
%A Scholz, Christoph
%A Skistims, Hendrik
%A Söllner, Matthias
%A Stumme, Gerd
%B {Socio-technical Design of Ubiquitous Computing Systems}
%C Heidelberg, Germany
%D 2014
%E David, Klaus
%E Geihs, Kurt
%E Leimeister, Jan-Marco
%E Roßnagel, Alexander
%E Schmidt, Ludger
%E Stumme, Gerd
%E Wacker, Arno
%I Springer Verlag
%T {Connect-U: A System for Enhancing Social Networking} - 1.Atzmueller, M., Ernst, A., Krebs, F., Scholz, C., Stumme, G.: On the Evolution of Social Groups During Coffee Breaks. In: [accepted/to appear] (ed.) 5th International Workshop on Modeling Social Media: Mining Big Data in Social Media at the 23rd International World Wide Web Conference, WWW 2014. , Seoul, South Korea (2014).
@inproceedings{atzmueller2014evolution,
address = {Seoul, South Korea},
author = {Atzmueller, Martin and Ernst, Andreas and Krebs, Friedrich and Scholz, Christoph and Stumme, Gerd},
booktitle = {5th International Workshop on Modeling Social Media: Mining Big Data in Social Media at the 23rd International World Wide Web Conference, WWW 2014},
editor = {[accepted/to appear]},
keywords = {face-to-face},
title = {On the Evolution of Social Groups During Coffee Breaks},
year = 2014
}%0 Conference Paper
%1 atzmueller2014evolution
%A Atzmueller, Martin
%A Ernst, Andreas
%A Krebs, Friedrich
%A Scholz, Christoph
%A Stumme, Gerd
%B 5th International Workshop on Modeling Social Media: Mining Big Data in Social Media at the 23rd International World Wide Web Conference, WWW 2014
%C Seoul, South Korea
%D 2014
%E [accepted/to appear],
%T On the Evolution of Social Groups During Coffee Breaks - 1.Scholz, C., Atzmueller, M., Stumme, G.: Unsupervised and Hybrid Approaches for On-Line RFID Localization with Mixed Context Knowledge. In: ISMIS (2014).
@inproceedings{DBLP:conf/ismis/SAS14,
author = {Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
booktitle = {ISMIS},
keywords = {itegpub},
title = {Unsupervised and Hybrid Approaches for On-Line RFID Localization with Mixed Context Knowledge},
year = 2014
}%0 Conference Paper
%1 DBLP:conf/ismis/SAS14
%A Scholz, Christoph
%A Atzmueller, Martin
%A Stumme, Gerd
%B ISMIS
%D 2014
%T Unsupervised and Hybrid Approaches for On-Line RFID Localization with Mixed Context Knowledge - 1.Hadgu, A.T., Jäschke, R.: Identifying and Analyzing Researchers on Twitter. In: Proceedings of the 2014 ACM Conference on Web Science. pp. 23–30. ACM, Bloomington, Indiana, USA (2014). https://doi.org/10.1145/2615569.2615676.For millions of users Twitter is an important communication platform, a social network, and a system for resource sharing. Likewise, scientists use Twitter to connect with other researchers, announce calls for papers, or share their thoughts. Filtering tweets, discovering other researchers, or finding relevant information on a topic of interest, however, is difficult since no directory of researchers on Twitter exists. In this paper we present an approach to identify Twitter accounts of researchers and demonstrate its utility for the discipline of computer science. Based on a seed set of computer science conferences we collect relevant Twitter users which we can partially map to ground-truth data. The mapping is leveraged to learn a model for classifying the remaining. To gain first insights into how researchers use Twitter, we empirically analyze the identified users and compare their age, popularity, influence, and social network.
@inproceedings{hadgu2014identifying,
abstract = {For millions of users Twitter is an important communication platform, a social network, and a system for resource sharing. Likewise, scientists use Twitter to connect with other researchers, announce calls for papers, or share their thoughts. Filtering tweets, discovering other researchers, or finding relevant information on a topic of interest, however, is difficult since no directory of researchers on Twitter exists. In this paper we present an approach to identify Twitter accounts of researchers and demonstrate its utility for the discipline of computer science. Based on a seed set of computer science conferences we collect relevant Twitter users which we can partially map to ground-truth data. The mapping is leveraged to learn a model for classifying the remaining. To gain first insights into how researchers use Twitter, we empirically analyze the identified users and compare their age, popularity, influence, and social network.},
address = {New York, NY, USA},
author = {Hadgu, Asmelash Teka and Jäschke, Robert},
booktitle = {Proceedings of the 2014 ACM Conference on Web Science},
keywords = {research},
pages = {23--30},
publisher = {ACM},
series = {WebSci '14},
title = {Identifying and Analyzing Researchers on Twitter},
year = 2014
}%0 Conference Paper
%1 hadgu2014identifying
%A Hadgu, Asmelash Teka
%A Jäschke, Robert
%B Proceedings of the 2014 ACM Conference on Web Science
%C New York, NY, USA
%D 2014
%I ACM
%P 23--30
%R 10.1145/2615569.2615676
%T Identifying and Analyzing Researchers on Twitter
%U http://doi.acm.org/10.1145/2615569.2615676
%X For millions of users Twitter is an important communication platform, a social network, and a system for resource sharing. Likewise, scientists use Twitter to connect with other researchers, announce calls for papers, or share their thoughts. Filtering tweets, discovering other researchers, or finding relevant information on a topic of interest, however, is difficult since no directory of researchers on Twitter exists. In this paper we present an approach to identify Twitter accounts of researchers and demonstrate its utility for the discipline of computer science. Based on a seed set of computer science conferences we collect relevant Twitter users which we can partially map to ground-truth data. The mapping is leveraged to learn a model for classifying the remaining. To gain first insights into how researchers use Twitter, we empirically analyze the identified users and compare their age, popularity, influence, and social network.
%@ 978-1-4503-2622-3 - 1.Jannach, D., Freyne, J., Geyer, W., Guy, I., Hotho, A., Mobasher, B.: The sixth {ACM} RecSys workshop on recommender systems and the social web. In: Eighth {ACM} Conference on Recommender Systems, RecSys ’14, Foster City, Silicon Valley, CA, {USA} - October 06 - 10, 2014. p. 395 (2014). https://doi.org/10.1145/2645710.2645786.
@inproceedings{jannach2014sixth,
author = {Jannach, Dietmar and Freyne, Jill and Geyer, Werner and Guy, Ido and Hotho, Andreas and Mobasher, Bamshad},
booktitle = {Eighth {ACM} Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, {USA} - October 06 - 10, 2014},
keywords = {introduction},
pages = 395,
title = {The sixth {ACM} RecSys workshop on recommender systems and the social web},
year = 2014
}%0 Conference Paper
%1 jannach2014sixth
%A Jannach, Dietmar
%A Freyne, Jill
%A Geyer, Werner
%A Guy, Ido
%A Hotho, Andreas
%A Mobasher, Bamshad
%B Eighth {ACM} Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, {USA} - October 06 - 10, 2014
%D 2014
%P 395
%R 10.1145/2645710.2645786
%T The sixth {ACM} RecSys workshop on recommender systems and the social web
%U http://doi.acm.org/10.1145/2645710.2645786 - 1.Doerfel, S., Zoller, D., Singer, P., Niebler, T., Hotho, A., Strohmaier, M.: Of course we share! Testing Assumptions about Social Tagging Systems, http://arxiv.org/abs/1401.0629, (2014).Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.
@misc{doerfel2014course,
abstract = {Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.},
author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
keywords = {share},
note = {cite arxiv:1401.0629},
title = {Of course we share! Testing Assumptions about Social Tagging Systems},
year = 2014
}%0 Generic
%1 doerfel2014course
%A Doerfel, Stephan
%A Zoller, Daniel
%A Singer, Philipp
%A Niebler, Thomas
%A Hotho, Andreas
%A Strohmaier, Markus
%D 2014
%T Of course we share! Testing Assumptions about Social Tagging Systems
%U http://arxiv.org/abs/1401.0629
%X Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior. - 1.Thiele, L., Atzmueller, M., Kauffeld, S., Stumme, G.: {Subjective versus Objective Captured Social Networks: Comparing Standard Self-Report Questionnaire Data with Observational RFID Technology Data}. In: Proc. Measuring Behavior. , Wageningen, The Netherlands (2014).
@inproceedings{TAKS:14,
address = {Wageningen, The Netherlands},
author = {Thiele, Lisa and Atzmueller, Martin and Kauffeld, Simone and Stumme, Gerd},
booktitle = {Proc. Measuring Behavior},
keywords = {itegpub},
title = {{Subjective versus Objective Captured Social Networks: Comparing Standard Self-Report Questionnaire Data with Observational RFID Technology Data}},
year = 2014
}%0 Conference Paper
%1 TAKS:14
%A Thiele, Lisa
%A Atzmueller, Martin
%A Kauffeld, Simone
%A Stumme, Gerd
%B Proc. Measuring Behavior
%C Wageningen, The Netherlands
%D 2014
%T {Subjective versus Objective Captured Social Networks: Comparing Standard Self-Report Questionnaire Data with Observational RFID Technology Data} - 1.Atzmueller, M., Scholz, C. eds.: {Proceedings of the 2014 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2014)}. ECML/PKDD 2014, Nancy, France (2014).
@book{AS:14,
address = {Nancy, France},
editor = {Atzmueller, Martin and Scholz, Christoph},
keywords = {muse},
publisher = {ECML/PKDD 2014},
title = {{Proceedings of the 2014 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2014)}},
year = 2014
}%0 Book
%1 AS:14
%C Nancy, France
%D 2014
%E Atzmueller, Martin
%E Scholz, Christoph
%I ECML/PKDD 2014
%T {Proceedings of the 2014 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2014)} - 1.Scholz, C., Macek, B.-E., Atzmueller, M., Doerfel, S., Stumme, G.: {Mining Social Links for Ubiquitous Knowledge Engineering}. In: David, K., Geihs, K., Leimeister, J.-M., Roßnagel, A., Schmidt, L., Stumme, G., and Wacker, A. (eds.) {Socio-technical Design of Ubiquitous Computing Systems}. Springer Verlag, Heidelberg, Germany (2014).
@incollection{SMADS:14,
address = {Heidelberg, Germany},
author = {Scholz, Christoph and Macek, Bjoern-Elmar and Atzmueller, Martin and Doerfel, Stephan and Stumme, Gerd},
booktitle = {{Socio-technical Design of Ubiquitous Computing Systems}},
editor = {David, Klaus and Geihs, Kurt and Leimeister, Jan-Marco and Roßnagel, Alexander and Schmidt, Ludger and Stumme, Gerd and Wacker, Arno},
keywords = {itegpub},
publisher = {Springer Verlag},
title = {{Mining Social Links for Ubiquitous Knowledge Engineering}},
year = 2014
}%0 Book Section
%1 SMADS:14
%A Scholz, Christoph
%A Macek, Bjoern-Elmar
%A Atzmueller, Martin
%A Doerfel, Stephan
%A Stumme, Gerd
%B {Socio-technical Design of Ubiquitous Computing Systems}
%C Heidelberg, Germany
%D 2014
%E David, Klaus
%E Geihs, Kurt
%E Leimeister, Jan-Marco
%E Roßnagel, Alexander
%E Schmidt, Ludger
%E Stumme, Gerd
%E Wacker, Arno
%I Springer Verlag
%T {Mining Social Links for Ubiquitous Knowledge Engineering} - 1.Scholz, C., Illig, J., Atzmueller, M., Stumme, G.: On the Predictability of Talk Attendance at Academic Conferences. In: Proceedings of the 25th ACM Conference on Hypertext and Social Media. pp. 279–284. ACM, Santiago, Chile (2014).This paper focuses on the prediction of real-world talk attendances at academic conferences with respect to different influence factors. We study and discuss the predictability of talk attendances using real-world face-to-face contact data and user interests extracted from the users' previous publications. For our experiments, we apply RFID-tracked talk attendance information captured at the ACM Conference on Hypertext and Hypermedia 2011. We find that contact and similarity networks achieve comparable results, and that combining these networks helps to a limited extent to improve the prediction quality.
@inproceedings{scholz2014predictability,
abstract = {This paper focuses on the prediction of real-world talk attendances at academic conferences with respect to different influence factors. We study and discuss the predictability of talk attendances using real-world face-to-face contact data and user interests extracted from the users' previous publications. For our experiments, we apply RFID-tracked talk attendance information captured at the ACM Conference on Hypertext and Hypermedia 2011. We find that contact and similarity networks achieve comparable results, and that combining these networks helps to a limited extent to improve the prediction quality.},
address = {Santiago, Chile},
author = {Scholz, Christoph and Illig, Jens and Atzmueller, Martin and Stumme, Gerd},
booktitle = {Proceedings of the 25th ACM Conference on Hypertext and Social Media},
keywords = {chile},
month = {09},
pages = {279--284},
publisher = {ACM},
series = {HT '14},
title = {On the Predictability of Talk Attendance at Academic Conferences},
year = 2014
}%0 Conference Paper
%1 scholz2014predictability
%A Scholz, Christoph
%A Illig, Jens
%A Atzmueller, Martin
%A Stumme, Gerd
%B Proceedings of the 25th ACM Conference on Hypertext and Social Media
%C Santiago, Chile
%D 2014
%I ACM
%P 279--284
%T On the Predictability of Talk Attendance at Academic Conferences
%X This paper focuses on the prediction of real-world talk attendances at academic conferences with respect to different influence factors. We study and discuss the predictability of talk attendances using real-world face-to-face contact data and user interests extracted from the users' previous publications. For our experiments, we apply RFID-tracked talk attendance information captured at the ACM Conference on Hypertext and Hypermedia 2011. We find that contact and similarity networks achieve comparable results, and that combining these networks helps to a limited extent to improve the prediction quality. - 1.Scholz, C., Illig, J., Atzmueller, M., Stumme, G.: {On the Predictability of Talk Attendance at Academic Conferences (Extended Abstract, Resubmission)}. In: Proc. LWA 2014 (KDML Special Track). RTWH Aachen University, Aachen, Germany (2014).
@inproceedings{SIAS:14b,
address = {Aachen, Germany},
author = {Scholz, Christoph and Illig, Jens and Atzmueller, Martin and Stumme, Gerd},
booktitle = {Proc. LWA 2014 (KDML Special Track)},
keywords = {itegpub},
publisher = {RTWH Aachen University},
title = {{On the Predictability of Talk Attendance at Academic Conferences (Extended Abstract, Resubmission)}},
year = 2014
}%0 Conference Paper
%1 SIAS:14b
%A Scholz, Christoph
%A Illig, Jens
%A Atzmueller, Martin
%A Stumme, Gerd
%B Proc. LWA 2014 (KDML Special Track)
%C Aachen, Germany
%D 2014
%I RTWH Aachen University
%T {On the Predictability of Talk Attendance at Academic Conferences (Extended Abstract, Resubmission)} - 1.Singer, P., Helic, D., Hotho, A., Strohmaier, M.: HypTrails: A Bayesian Approach for Comparing Hypotheses about Human Trails on the Web, http://arxiv.org/abs/1411.2844, (2014).When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful for e.g., improving underlying network structures, predicting user clicks or enhancing recommendations. In this work, we present a general approach called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our approach utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to leverage the sensitivity of Bayes factors on the prior for comparing hypotheses with each other. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including website navigation, business reviews and online music played. Our work expands the repertoire of methods available for studying human trails on the Web.
@misc{singer2014hyptrails,
abstract = {When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful for e.g., improving underlying network structures, predicting user clicks or enhancing recommendations. In this work, we present a general approach called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our approach utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to leverage the sensitivity of Bayes factors on the prior for comparing hypotheses with each other. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including website navigation, business reviews and online music played. Our work expands the repertoire of methods available for studying human trails on the Web.},
author = {Singer, Philipp and Helic, Denis and Hotho, Andreas and Strohmaier, Markus},
keywords = {hypotheses},
note = {cite arxiv:1411.2844},
title = {HypTrails: A Bayesian Approach for Comparing Hypotheses about Human Trails on the Web},
year = 2014
}%0 Generic
%1 singer2014hyptrails
%A Singer, Philipp
%A Helic, Denis
%A Hotho, Andreas
%A Strohmaier, Markus
%D 2014
%T HypTrails: A Bayesian Approach for Comparing Hypotheses about Human Trails on the Web
%U http://arxiv.org/abs/1411.2844
%X When users interact with the Web today, they leave sequential digital trails on a massive scale. Examples of such human trails include Web navigation, sequences of online restaurant reviews, or online music play lists. Understanding the factors that drive the production of these trails can be useful for e.g., improving underlying network structures, predicting user clicks or enhancing recommendations. In this work, we present a general approach called HypTrails for comparing a set of hypotheses about human trails on the Web, where hypotheses represent beliefs about transitions between states. Our approach utilizes Markov chain models with Bayesian inference. The main idea is to incorporate hypotheses as informative Dirichlet priors and to leverage the sensitivity of Bayes factors on the prior for comparing hypotheses with each other. For eliciting Dirichlet priors from hypotheses, we present an adaption of the so-called (trial) roulette method. We demonstrate the general mechanics and applicability of HypTrails by performing experiments with (i) synthetic trails for which we control the mechanisms that have produced them and (ii) empirical trails stemming from different domains including website navigation, business reviews and online music played. Our work expands the repertoire of methods available for studying human trails on the Web. - 1.David, K., Geihs, K., Leimeister, J.M., Roßnagel, A., Schmidt, L., Stumme, G., Wacker, A. eds.: Socio-technical design of ubiquitous computing systems. Springer (2014).By using various data inputs, ubiquitous computing systems detect their current usage context, automatically adapt their services to the user's situational needs and interact with other services or resources in their environment on an ad-hoc basis. Designing such self-adaptive, context-aware knowledge processing systems is, in itself, a formidable challenge. This book presents core findings from the VENUS project at the Interdisciplinary Research Center for Information System Design (ITeG) at Kassel University, where researchers from different fields, such as computer science, information systems, human-computer interaction and law, together seek to find general principles and guidelines for the design of socially aware ubiquitous computing systems. To this end, system usability, user trust in the technology and adherence to privacy laws and regulations were treated as particularly important criteria in the context of socio-technical system design. During the project, a comprehensive blueprint for systematic, interdisciplinary software development was developed, covering the particular functional and non-functional design aspects of ubiquitous computing at the interface between technology and human beings. The organization of the book reflects the structure of the VENUS work program. After an introductory part I, part II provides the groundwork for VENUS by presenting foundational results from all four disciplines involved. Subsequently, part III focuses on methodological research funneling the development activities into a common framework. Part IV then covers the design of the demonstrators that were built in order to develop and evaluate the VENUS method. Finally, part V is dedicated to the evaluation phase to assess the user acceptance of the new approach and applications. The presented findings are especially important for researchers in computer science, information systems, and human-computer interaction, but also for everyone working on the acceptance of new technologies in society in general.
@book{david2014sociotechnical,
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%@ 9783319050447 3319050443 3319050435 9783319050430 - 1.Scholz, C., Atzmueller, M., Stumme, G.: {Predictability of Evolving Contacts and Triadic Closure in Human Face-to-Face Proximity Networks}. Journal of Social Network Analysis and Mining. 4, (2014).
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%V 4 - 1.Doerfel, S., Zoller, D., Singer, P., Niebler, T., Hotho, A., Strohmaier, M.: How Social is Social Tagging?. In: Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion. pp. 251–252. International World Wide Web Conferences Steering Committee, Seoul, Korea (2014). https://doi.org/10.1145/2567948.2577301.Social tagging systems have established themselves as an important part in today's web and have attracted the interest of our research community in a variety of investigations. This has led to several assumptions about tagging, such as that tagging systems exhibit a social component. In this work we overcome the previous absence of data for testing such an assumption. We thoroughly study social interaction, leveraging for the first time live log data gathered from the real-world public social tagging system \bibs. Our results indicate that sharing of resources constitutes an important and indeed social aspect of tagging.
@inproceedings{doerfel2014social,
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%X Social tagging systems have established themselves as an important part in today's web and have attracted the interest of our research community in a variety of investigations. This has led to several assumptions about tagging, such as that tagging systems exhibit a social component. In this work we overcome the previous absence of data for testing such an assumption. We thoroughly study social interaction, leveraging for the first time live log data gathered from the real-world public social tagging system \bibs. Our results indicate that sharing of resources constitutes an important and indeed social aspect of tagging.
%@ 978-1-4503-2745-9 - 1.Atzmüller, M., Baraki, H., Behrenbruch, K., Comes, D., Evers, C., Hoffmann, A., Hoffmann, H., Jandt, S., Kibanov, M., Kieselmann, O., Kniewel, R., König, I., Macek, B., Niemczyk, S., Scholz, C., Schuldt, M., Schulz, T., Skistims, H., Söllner, M., Voigtmann, C., Witsch, A., Zirfas, J.: Die VENUS-Entwicklungsmethode - Eine interdisziplinäre Methode für soziotechnische Softwaregestaltung. Kassel University Press (2014).
@techreport{atzmuller2014venusentwicklungsmethode,
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%V 1 - 1.Scholz, C., Illig, J., Atzmueller, M., Stumme, G.: {On the Predictability of Talk Attendance at Academic Conferences (Extended Abstract)}. In: Proc. LWA 2014 (KDML Special Track). RTWH Aachen University, Aachen, Germany (2014).
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%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2014-lwa-kdml-talk-prediction-extended-abstract.pdf - 1.Atzmueller, M.: {Mining Social Interaction -- Ubiquitous Sensors and Social Media}. In: Proc. International Conference on Future RFID Technologies. pp. 5–13. , Eger, Hungary (2014).
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%T {Mining Social Interaction -- Ubiquitous Sensors and Social Media} - 1.Atzmueller, M., Bobek, S., Kibanov, M., Nalepa, G.J.: {Towards Context Detection in the Ambient Classroom using Wearable Sensors}. In: Proceedings of the 2014 International Smart University Workshop (SmartU 2014), London, UK. , London, UK (2014).
@inproceedings{ABKN:14,
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%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-smartuni14-paper7.pdf - 1.Blümel, I., Hauschke, C., Jäschke, R.: Literatur recherchieren und verwalten. In: CoScience - Gemeinsam forschen und publizieren mit dem Netz. pp. 12–20. Technische Informationsbibliothek, Hannover (2014). https://doi.org/10.2314/coscv1.1.Ob in Forschungs- oder Publikationsprojekten - Recherche ist essentieller Bestandteil im Prozess des wissenschaftlichen Arbeitens, und das nicht nur am Anfang eines Projektes, sondern immer wieder und zu unterschiedlichen Projektmomenten. Wer forscht, möchte wissen, was schon geforscht wurde, welche Methoden für ein Projekt anwendbar sind, welche Begrifflichkeiten verwendet werden und welche inhaltlichen, formalen und methodischen Klippen es gegebenenfalls zu umschiffen gilt. Die Verwaltung der gefundenen Quellen ist Teil der Recherche und, unter anderem, eine wichtige Voraussetzung für korrektes Zitieren. Beim kollaborativen Arbeiten ist das Teilen der recherchierten Information wünschenswert, um den Wissenstand zu homogenisieren und Doppelarbeit zu vermeiden. In vernetzten Projekten besteht die Besonderheit darin, die Recherche so durchzuführen, dass das Ergebnis, also die gefundenen Informationen, allen Projektmitgliedern transparent ist.
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%& 1 - 1.Scholz, C., Atzmueller, M., Stumme, G.: Link Prediction and the Role of Stronger Ties in Networks of Face-to-Face Proximity. CoRR. abs/1407.2161, (2014).
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%V abs/1407.2161 - 1.Atzmueller, M., Behrenbruch, K., Hoffmann, A., Kibanov, M., Macek, B.-E., Scholz, C., Skistims, H., Söllner, M., Stumme, G.: {Socio-technical Design of Ubiquitous Computing Systems}. Presented at the , Heidelberg, Germany (2014).
@incollection{atzmueller2014sociotechnical,
address = {Heidelberg, Germany},
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chapter = {{Connect-U: A System for Enhancing Social Networking}},
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%& {Connect-U: A System for Enhancing Social Networking} - 1.Mitzlaff, F., Atzmueller, M., Hotho, A., Stumme, G.: {The Social Distributional Hypothesis}. Journal of Social Network Analysis and Mining. 4, (2014).
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%V 4 - 1.Singer, P., Niebler, T., Hotho, A., Strohmaier, M.: Folksonomies. In: Encyclopedia of Social Network Analysis and Mining. pp. 542–547. Springer (2014).
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%T Folksonomies - 1.Atzmueller, M.: {Analyzing and Grounding Social Interaction in Online and Offline Networks}. In: Proc. ECML/PKDD 2014: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. pp. 485–488. Springer Verlag, Heidelberg, Germany (2014).
@inproceedings{Atzmueller:14:Nectar,
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%V 8726 - 1.Atzmueller, M., Chin, A., Trattner, C. eds.: {Proceedings MSM 2014: Workshop on Modeling Social Media - Mining Big Data in Social Media and the Web}. ACM Press, New York, NY, USA (2014).
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%T {Proceedings MSM 2014: Workshop on Modeling Social Media - Mining Big Data in Social Media and the Web} - 1.Atzmueller, M., Thiele, L., Stumme, G., Kauffeld, S.: {Evolution and Dynamics of Student Interaction on Networks of Face-to-Face Proximity}. In: Proceedings of the 2014 International Smart University Workshop (SmartU 2014), London, UK. , London, UK (2014).
@inproceedings{ATSK:14,
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%C London, UK
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%T {Evolution and Dynamics of Student Interaction on Networks of Face-to-Face Proximity} - 1.Mitzlaff, F., Atzmueller, M., Hotho, A., Stumme, G.: The social distributional hypothesis: a pragmatic proxy for homophily in online social networks. Social Network Analysis and Mining. 4, (2014). https://doi.org/10.1007/s13278-014-0216-2.Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the
@article{mitzlaff2014social,
abstract = {Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the},
author = {Mitzlaff, Folke and Atzmueller, Martin and Hotho, Andreas and Stumme, Gerd},
journal = {Social Network Analysis and Mining},
keywords = {itegpub},
number = 1,
publisher = {Springer Vienna},
title = {The social distributional hypothesis: a pragmatic proxy for homophily in online social networks},
volume = 4,
year = 2014
}%0 Journal Article
%1 mitzlaff2014social
%A Mitzlaff, Folke
%A Atzmueller, Martin
%A Hotho, Andreas
%A Stumme, Gerd
%D 2014
%I Springer Vienna
%J Social Network Analysis and Mining
%N 1
%R 10.1007/s13278-014-0216-2
%T The social distributional hypothesis: a pragmatic proxy for homophily in online social networks
%U http://dx.doi.org/10.1007/s13278-014-0216-2
%V 4
%X Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the - 1.Doerfel, S., Zoller, D., Singer, P., Niebler, T., Hotho, A., Strohmaier, M.: Evaluating Assumptions about Social Tagging - A Study of User Behavior in BibSonomy. In: Seidl, T., Hassani, M., and Beecks, C. (eds.) Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014. pp. 18–19. CEUR-WS.org (2014).Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several assumptions about social tagging systems have emerged on which our community also builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we investigate and evaluate four assumptions about tagging systems by examining live server log data gathered from the public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected in a very critical light.
@inproceedings{doerfel2014evaluating,
abstract = {Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several assumptions about social tagging systems have emerged on which our community also builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we investigate and evaluate four assumptions about tagging systems by examining live server log data gathered from the public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected in a very critical light.},
author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
booktitle = {Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014.},
editor = {Seidl, Thomas and Hassani, Marwan and Beecks, Christian},
keywords = {behavior},
pages = {18-19},
publisher = {CEUR-WS.org},
title = {Evaluating Assumptions about Social Tagging - A Study of User Behavior in BibSonomy},
year = 2014
}%0 Conference Paper
%1 doerfel2014evaluating
%A Doerfel, Stephan
%A Zoller, Daniel
%A Singer, Philipp
%A Niebler, Thomas
%A Hotho, Andreas
%A Strohmaier, Markus
%B Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014.
%D 2014
%E Seidl, Thomas
%E Hassani, Marwan
%E Beecks, Christian
%I CEUR-WS.org
%P 18-19
%T Evaluating Assumptions about Social Tagging - A Study of User Behavior in BibSonomy
%U http://ceur-ws.org/Vol-1226/
%X Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several assumptions about social tagging systems have emerged on which our community also builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we investigate and evaluate four assumptions about tagging systems by examining live server log data gathered from the public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected in a very critical light. - 1.Doerfel, S., Hotho, A., Jäschke, R., Mitzlaff, F., Mueller, J. eds.: ECML PKDD Discovery Challenge - Recommending Given Names. CEUR-WS (2014).All over the world, future parents are facing the task of finding a suitable given name for their children. Their choice is usually influenced by a variety of factors, such as the social context, language, cultural background and especially personal taste. Although this task is omnipresent, little research has been conducted on the analysis and application of interrelations among given names from a data mining perspective. Since 1999 the ECML PKDD embraces the tradition of organizing a Discovery Challenge, allowing researchers to develop and test algorithms for novel and real world datasets. The Discovery Challenge 20131 tackled the task of recommending given names in the context of the name search engine Nameling. It consisted of an offline and an online phase. In both phases, participants were asked to create a name recommendation algorithm that could provide suitable suggestions of given names to users of Nameling. More than 40 participants/teams registered for the challenge, of which 17 handed in predictions of the offline challenge. After the end of the offline phase 6 teams submitted a paper. All papers have been peer reviewed and can be found in these proceedings. The different approaches to the challenge are presented at the ECML PKDD workshop on September 27th, 2013, in Prague, Czech Republic. The online challenge ran until the day before the workshop and four teams successfully participated with implementations meeting all required criteria. Details of the two challenge tasks, winners of both phases and an overview of the main findings are presented in the first paper of these proceedings.
@proceedings{doerfel2014discovery,
abstract = {All over the world, future parents are facing the task of finding a suitable given name for their children. Their choice is usually influenced by a variety of factors, such as the social context, language, cultural background and especially personal taste. Although this task is omnipresent, little research has been conducted on the analysis and application of interrelations among given names from a data mining perspective. Since 1999 the ECML PKDD embraces the tradition of organizing a Discovery Challenge, allowing researchers to develop and test algorithms for novel and real world datasets. The Discovery Challenge 20131 tackled the task of recommending given names in the context of the name search engine Nameling. It consisted of an offline and an online phase. In both phases, participants were asked to create a name recommendation algorithm that could provide suitable suggestions of given names to users of Nameling. More than 40 participants/teams registered for the challenge, of which 17 handed in predictions of the offline challenge. After the end of the offline phase 6 teams submitted a paper. All papers have been peer reviewed and can be found in these proceedings. The different approaches to the challenge are presented at the ECML PKDD workshop on September 27th, 2013, in Prague, Czech Republic. The online challenge ran until the day before the workshop and four teams successfully participated with implementations meeting all required criteria. Details of the two challenge tasks, winners of both phases and an overview of the main findings are presented in the first paper of these proceedings.},
editor = {Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Mitzlaff, Folke and Mueller, Juergen},
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volume = 1120,
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}%0 Conference Proceedings
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%E Doerfel, Stephan
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%U http://ceur-ws.org/Vol-1120/
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%X All over the world, future parents are facing the task of finding a suitable given name for their children. Their choice is usually influenced by a variety of factors, such as the social context, language, cultural background and especially personal taste. Although this task is omnipresent, little research has been conducted on the analysis and application of interrelations among given names from a data mining perspective. Since 1999 the ECML PKDD embraces the tradition of organizing a Discovery Challenge, allowing researchers to develop and test algorithms for novel and real world datasets. The Discovery Challenge 20131 tackled the task of recommending given names in the context of the name search engine Nameling. It consisted of an offline and an online phase. In both phases, participants were asked to create a name recommendation algorithm that could provide suitable suggestions of given names to users of Nameling. More than 40 participants/teams registered for the challenge, of which 17 handed in predictions of the offline challenge. After the end of the offline phase 6 teams submitted a paper. All papers have been peer reviewed and can be found in these proceedings. The different approaches to the challenge are presented at the ECML PKDD workshop on September 27th, 2013, in Prague, Czech Republic. The online challenge ran until the day before the workshop and four teams successfully participated with implementations meeting all required criteria. Details of the two challenge tasks, winners of both phases and an overview of the main findings are presented in the first paper of these proceedings. - 1.Yang, S., Lerman, K., She, J., Atzmueller, M. eds.: {Proceedings of the 2014 International Conference on Social Computing, Beijing, China, August 04 - 07, 2014}. {ACM} (2014).
@proceedings{YLSA:14,
editor = {Yang, Su and Lerman, Kristina and She, James and Atzmueller, Martin},
keywords = {itegpub},
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title = {{Proceedings of the 2014 International Conference on Social Computing, Beijing, China, August 04 - 07, 2014}},
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}%0 Conference Proceedings
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%@ 978-1-4503-2888-3 - 1.Jannach, D., Freyne, J., Geyer, W., Guy, I., Hotho, A., Mobasher, B. eds.: Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th {ACM} Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014. CEUR-WS.org (2014).
@proceedings{jannach2014proceedings,
editor = {Jannach, Dietmar and Freyne, Jill and Geyer, Werner and Guy, Ido and Hotho, Andreas and Mobasher, Bamshad},
keywords = {recommender},
publisher = {CEUR-WS.org},
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title = {Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th {ACM} Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014},
volume = 1271,
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}%0 Conference Proceedings
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%E Geyer, Werner
%E Guy, Ido
%E Hotho, Andreas
%E Mobasher, Bamshad
%I CEUR-WS.org
%T Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th {ACM} Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014
%U http://ceur-ws.org/Vol-1271
%V 1271 - 1.Cellier, P., Charnois, T., Hotho, A., Matwin, S., Moens, M.- }Francine, Toussaint, Y. eds.: Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014. CEUR-WS.org (2014).
@proceedings{cellier2014proceedings,
editor = {Cellier, Peggy and Charnois, Thierry and Hotho, Andreas and Matwin, Stan and Moens, Marie{-}Francine and Toussaint, Yannick},
keywords = {workshop},
publisher = {CEUR-WS.org},
series = {{CEUR} Workshop Proceedings},
title = {Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014},
volume = 1202,
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}%0 Conference Proceedings
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%E Charnois, Thierry
%E Hotho, Andreas
%E Matwin, Stan
%E Moens, Marie{-}Francine
%E Toussaint, Yannick
%I CEUR-WS.org
%T Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014
%U http://ceur-ws.org/Vol-1202
%V 1202 - 1.Scholz, C., Atzmueller, M., Stumme, G.: On the Predictability of Recurring Links in Networks of Face-to-Face Proximity. In: [accepted/to appear] (ed.) 5th International Workshop on Modeling Social Media: Mining Big Data in Social Media at the 23rd International World Wide Web Conference, WWW 2014. , Seoul, South Korea (2014).
@inproceedings{scholz2014predictability,
address = {Seoul, South Korea},
author = {Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
booktitle = {5th International Workshop on Modeling Social Media: Mining Big Data in Social Media at the 23rd International World Wide Web Conference, WWW 2014},
editor = {[accepted/to appear]},
keywords = {face-to-face},
title = {On the Predictability of Recurring Links in Networks of Face-to-Face Proximity},
year = 2014
}%0 Conference Paper
%1 scholz2014predictability
%A Scholz, Christoph
%A Atzmueller, Martin
%A Stumme, Gerd
%B 5th International Workshop on Modeling Social Media: Mining Big Data in Social Media at the 23rd International World Wide Web Conference, WWW 2014
%C Seoul, South Korea
%D 2014
%E [accepted/to appear],
%T On the Predictability of Recurring Links in Networks of Face-to-Face Proximity
2013
- 1.Niebler, T., Singer, P., Benz, D., Körner, C., Strohmaier, M., Hotho, A.: How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems. In: Serdyukov, P., Braslavski, P., Kuznetsov, S., Kamps, J., Rüger, S., Agichtein, E., Segalovich, I., and Yilmaz, E. (eds.) Advances in Information Retrieval. pp. 86–97. Springer Berlin Heidelberg (2013). https://doi.org/10.1007/978-3-642-36973-5_8.The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which
@incollection{niebler2013tagging,
abstract = {The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which},
author = {Niebler, Thomas and Singer, Philipp and Benz, Dominik and Körner, Christian and Strohmaier, Markus and Hotho, Andreas},
booktitle = {Advances in Information Retrieval},
editor = {Serdyukov, Pavel and Braslavski, Pavel and Kuznetsov, SergeiO. and Kamps, Jaap and Rüger, Stefan and Agichtein, Eugene and Segalovich, Ilya and Yilmaz, Emine},
keywords = {sense},
pages = {86-97},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
title = {How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems},
volume = 7814,
year = 2013
}%0 Book Section
%1 niebler2013tagging
%A Niebler, Thomas
%A Singer, Philipp
%A Benz, Dominik
%A Körner, Christian
%A Strohmaier, Markus
%A Hotho, Andreas
%B Advances in Information Retrieval
%D 2013
%E Serdyukov, Pavel
%E Braslavski, Pavel
%E Kuznetsov, SergeiO.
%E Kamps, Jaap
%E Rüger, Stefan
%E Agichtein, Eugene
%E Segalovich, Ilya
%E Yilmaz, Emine
%I Springer Berlin Heidelberg
%P 86-97
%R 10.1007/978-3-642-36973-5_8
%T How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems
%U http://dx.doi.org/10.1007/978-3-642-36973-5_8
%V 7814
%X The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which
%@ 978-3-642-36972-8 - 1.Becker, M., Caminiti, S., Fiorella, D., Francis, L., Gravino, P., Haklay, M. (Muki), Hotho, A., Loreto, V., Mueller, J., Ricchiuti, F., Servedio, V.D.P., Sîrbu, A., Tria, F.: Awareness and Learning in Participatory Noise Sensing. PLOS ONE. 8, e81638 (2013). https://doi.org/10.1371/journal.pone.0081638.The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.
@article{mueller-2013d,
abstract = {The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.},
author = {Becker, Martin and Caminiti, Saverio and Fiorella, Donato and Francis, Louise and Gravino, Pietro and Haklay, Mordechai (Muki) and Hotho, Andreas and Loreto, Vittorio and Mueller, Juergen and Ricchiuti, Ferdinando and Servedio, Vito D. P. and Sîrbu, Alina and Tria, Francesca},
journal = {PLOS ONE},
keywords = {EveryAware},
month = 12,
number = 12,
pages = {e81638},
title = {Awareness and Learning in Participatory Noise Sensing},
volume = 8,
year = 2013
}%0 Journal Article
%1 mueller-2013d
%A Becker, Martin
%A Caminiti, Saverio
%A Fiorella, Donato
%A Francis, Louise
%A Gravino, Pietro
%A Haklay, Mordechai (Muki)
%A Hotho, Andreas
%A Loreto, Vittorio
%A Mueller, Juergen
%A Ricchiuti, Ferdinando
%A Servedio, Vito D. P.
%A Sîrbu, Alina
%A Tria, Francesca
%D 2013
%J PLOS ONE
%N 12
%P e81638
%R 10.1371/journal.pone.0081638
%T Awareness and Learning in Participatory Noise Sensing
%U http://dx.doi.org/10.1371/journal.pone.0081638
%V 8
%X The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments. - 1.Jäschke, R., Rudolph, S.: Attribute Exploration on the Web. In: Cellier, P., Distel, F., and Ganter, B. (eds.) Contributions to the 11th International Conference on Formal Concept Analysis. pp. 19–34. Technische Universität Dresden (2013).We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.
@inproceedings{jaeschke2013attribute,
abstract = {We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.},
author = {Jäschke, Robert and Rudolph, Sebastian},
booktitle = {Contributions to the 11th International Conference on Formal Concept Analysis},
editor = {Cellier, Peggy and Distel, Felix and Ganter, Bernhard},
keywords = {linked},
month = {05},
organization = {Technische Universität Dresden},
pages = {19--34},
title = {Attribute Exploration on the Web},
year = 2013
}%0 Conference Paper
%1 jaeschke2013attribute
%A Jäschke, Robert
%A Rudolph, Sebastian
%B Contributions to the 11th International Conference on Formal Concept Analysis
%D 2013
%E Cellier, Peggy
%E Distel, Felix
%E Ganter, Bernhard
%P 19--34
%T Attribute Exploration on the Web
%U http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113133
%X We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted. - 1.Mitzlaff, F.: Name Me If You Can(!) - Leveraging Networks of Given Names. In: Proceedings from Sunbelt XXXIII (2013).
@inproceedings{mitzlaff2013leveraging,
author = {Mitzlaff, Folke},
booktitle = {Proceedings from Sunbelt XXXIII},
keywords = {nameling},
title = {Name Me If You Can(!) - Leveraging Networks of Given Names},
year = 2013
}%0 Conference Paper
%1 mitzlaff2013leveraging
%A Mitzlaff, Folke
%B Proceedings from Sunbelt XXXIII
%D 2013
%T Name Me If You Can(!) - Leveraging Networks of Given Names - 1.Landia, N., Doerfel, S., Jäschke, R., Anand, S.S., Hotho, A., Griffiths, N.: Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations. cs.IR. 1310.1498, (2013).The information contained in social tagging systems is often modelled as a graph of connections between users, items and tags. Recommendation algorithms such as FolkRank, have the potential to leverage complex relationships in the data, corresponding to multiple hops in the graph. We present an in-depth analysis and evaluation of graph models for social tagging data and propose novel adaptations and extensions of FolkRank to improve tag recommendations. We highlight implicit assumptions made by the widely used folksonomy model, and propose an alternative and more accurate graph-representation of the data. Our extensions of FolkRank address the new item problem by incorporating content data into the algorithm, and significantly improve prediction results on unpruned datasets. Our adaptations address issues in the iterative weight spreading calculation that potentially hinder FolkRank's ability to leverage the deep graph as an information source. Moreover, we evaluate the benefit of considering each deeper level of the graph, and present important insights regarding the characteristics of social tagging data in general. Our results suggest that the base assumption made by conventional weight propagation methods, that closeness in the graph always implies a positive relationship, does not hold for the social tagging domain.
@article{landia2013deeper,
abstract = {The information contained in social tagging systems is often modelled as a graph of connections between users, items and tags. Recommendation algorithms such as FolkRank, have the potential to leverage complex relationships in the data, corresponding to multiple hops in the graph. We present an in-depth analysis and evaluation of graph models for social tagging data and propose novel adaptations and extensions of FolkRank to improve tag recommendations. We highlight implicit assumptions made by the widely used folksonomy model, and propose an alternative and more accurate graph-representation of the data. Our extensions of FolkRank address the new item problem by incorporating content data into the algorithm, and significantly improve prediction results on unpruned datasets. Our adaptations address issues in the iterative weight spreading calculation that potentially hinder FolkRank's ability to leverage the deep graph as an information source. Moreover, we evaluate the benefit of considering each deeper level of the graph, and present important insights regarding the characteristics of social tagging data in general. Our results suggest that the base assumption made by conventional weight propagation methods, that closeness in the graph always implies a positive relationship, does not hold for the social tagging domain.},
author = {Landia, Nikolas and Doerfel, Stephan and Jäschke, Robert and Anand, Sarabjot Singh and Hotho, Andreas and Griffiths, Nathan},
journal = {cs.IR},
keywords = {bookmarking},
title = {Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations},
volume = {1310.1498},
year = 2013
}%0 Journal Article
%1 landia2013deeper
%A Landia, Nikolas
%A Doerfel, Stephan
%A Jäschke, Robert
%A Anand, Sarabjot Singh
%A Hotho, Andreas
%A Griffiths, Nathan
%D 2013
%J cs.IR
%T Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations
%U http://arxiv.org/abs/1310.1498
%V 1310.1498
%X The information contained in social tagging systems is often modelled as a graph of connections between users, items and tags. Recommendation algorithms such as FolkRank, have the potential to leverage complex relationships in the data, corresponding to multiple hops in the graph. We present an in-depth analysis and evaluation of graph models for social tagging data and propose novel adaptations and extensions of FolkRank to improve tag recommendations. We highlight implicit assumptions made by the widely used folksonomy model, and propose an alternative and more accurate graph-representation of the data. Our extensions of FolkRank address the new item problem by incorporating content data into the algorithm, and significantly improve prediction results on unpruned datasets. Our adaptations address issues in the iterative weight spreading calculation that potentially hinder FolkRank's ability to leverage the deep graph as an information source. Moreover, we evaluate the benefit of considering each deeper level of the graph, and present important insights regarding the characteristics of social tagging data in general. Our results suggest that the base assumption made by conventional weight propagation methods, that closeness in the graph always implies a positive relationship, does not hold for the social tagging domain. - 1.Atzmueller, M., Chin, A., Helic, D., Hotho, A. eds.: Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers. Imprint: Springer, Berlin, Heidelberg (2013).
@book{atzmueller2013ubiquitous,
address = {Berlin, Heidelberg},
editor = {Atzmueller, Martin and Chin, Alvin and Helic, Denis and Hotho, Andreas},
keywords = {bibsonomy},
publisher = {Imprint: Springer},
title = {Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers},
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}%0 Book
%1 atzmueller2013ubiquitous
%C Berlin, Heidelberg
%D 2013
%E Atzmueller, Martin
%E Chin, Alvin
%E Helic, Denis
%E Hotho, Andreas
%I Imprint: Springer
%T Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers
%U http://link.springer.com/book/10.1007/978-3-642-45392-2
%@ 9783642453915 3642453910 9783642453922 3642453929 - 1.Mueller, J., Doerfel, S., Becker, M., Hotho, A., Stumme, G.: Tag Recommendations for SensorFolkSonomies. In: Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings. CEUR-WS, Aachen, Germany (2013).With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.
@inproceedings{mueller2013recommendations,
abstract = {With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case.},
address = {Aachen, Germany},
author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd},
booktitle = {Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings},
keywords = {recommender},
publisher = {CEUR-WS},
title = {Tag Recommendations for SensorFolkSonomies},
volume = 1066,
year = 2013
}%0 Conference Paper
%1 mueller2013recommendations
%A Mueller, Juergen
%A Doerfel, Stephan
%A Becker, Martin
%A Hotho, Andreas
%A Stumme, Gerd
%B Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings
%C Aachen, Germany
%D 2013
%I CEUR-WS
%T Tag Recommendations for SensorFolkSonomies
%U http://ceur-ws.org/Vol-1066/
%V 1066
%X With the rising popularity of smart mobile devices, sensor data-based applications have become more and more popular. Their users record data during their daily routine or specifically for certain events. The application WideNoise Plus allows users to record sound samples and to annotate them with perceptions and tags. The app is being used to document and map the soundscape all over the world. The procedure of recording, including the assignment of tags, has to be as easy-to-use as possible. We therefore discuss the application of tag recommender algorithms in this particular scenario. We show, that this task is fundamentally different from the well-known tag recommendation problem in folksonomies as users do no longer tag fix resources but rather sensory data and impressions. The scenario requires efficient recommender algorithms that are able to run on the mobile device, since Internet connectivity cannot be assumed to be available. Therefore, we evaluate the performance of several tag recommendation algorithms and discuss their applicability in the mobile sensing use-case. - 1.Becker, M., Mueller, J., Hotho, A., Stumme, G.: A Generic Platform for Ubiquitous and Subjective Data. In: 1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland -- September 9, 2013. Proceedings. p. New York, NY, USA. ACM (2013).An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform.
@inproceedings{mueller-2013a,
abstract = {An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform.},
author = {Becker, Martin and Mueller, Juergen and Hotho, Andreas and Stumme, Gerd},
booktitle = {1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland -- September 9, 2013. Proceedings},
keywords = {platform},
note = {Accepted for publication},
pages = {New York, NY, USA},
publisher = {ACM},
title = {A Generic Platform for Ubiquitous and Subjective Data},
year = 2013
}%0 Conference Paper
%1 mueller-2013a
%A Becker, Martin
%A Mueller, Juergen
%A Hotho, Andreas
%A Stumme, Gerd
%B 1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland -- September 9, 2013. Proceedings
%D 2013
%I ACM
%P New York, NY, USA
%T A Generic Platform for Ubiquitous and Subjective Data
%X An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform. - 1.Mitzlaff, F., Stumme, G.: Recommending Given Names, http://arxiv.org/abs/1302.4412, (2013).All over the world, future parents are facing the task of finding a suitable given name for their child. This choice is influenced by different factors, such as the social context, language, cultural background and especially personal taste. Although this task is omnipresent, little research has been conducted on the analysis and application of interrelations among given names from a data mining perspective. The present work tackles the problem of recommending given names, by firstly mining for inter-name relatedness in data from the Social Web. Based on these results, the name search engine "Nameling" was built, which attracted more than 35,000 users within less than six months, underpinning the relevance of the underlying recommendation task. The accruing usage data is then used for evaluating different state-of-the-art recommendation systems, as well our new \NR algorithm which we adopted from our previous work on folksonomies and which yields the best results, considering the trade-off between prediction accuracy and runtime performance as well as its ability to generate personalized recommendations. We also show, how the gathered inter-name relationships can be used for meaningful result diversification of PageRank-based recommendation systems. As all of the considered usage data is made publicly available, the present work establishes baseline results, encouraging other researchers to implement advanced recommendation systems for given names.
@misc{mitzlaff2013recommending,
abstract = {All over the world, future parents are facing the task of finding a suitable given name for their child. This choice is influenced by different factors, such as the social context, language, cultural background and especially personal taste. Although this task is omnipresent, little research has been conducted on the analysis and application of interrelations among given names from a data mining perspective. The present work tackles the problem of recommending given names, by firstly mining for inter-name relatedness in data from the Social Web. Based on these results, the name search engine "Nameling" was built, which attracted more than 35,000 users within less than six months, underpinning the relevance of the underlying recommendation task. The accruing usage data is then used for evaluating different state-of-the-art recommendation systems, as well our new \NR algorithm which we adopted from our previous work on folksonomies and which yields the best results, considering the trade-off between prediction accuracy and runtime performance as well as its ability to generate personalized recommendations. We also show, how the gathered inter-name relationships can be used for meaningful result diversification of PageRank-based recommendation systems. As all of the considered usage data is made publicly available, the present work establishes baseline results, encouraging other researchers to implement advanced recommendation systems for given names.},
author = {Mitzlaff, Folke and Stumme, Gerd},
keywords = {nameling},
note = {cite arxiv:1302.4412Comment: Baseline results for the ECML PKDD Discovery Challenge 2013},
title = {Recommending Given Names},
year = 2013
}%0 Generic
%1 mitzlaff2013recommending
%A Mitzlaff, Folke
%A Stumme, Gerd
%D 2013
%T Recommending Given Names
%U http://arxiv.org/abs/1302.4412
%X All over the world, future parents are facing the task of finding a suitable given name for their child. This choice is influenced by different factors, such as the social context, language, cultural background and especially personal taste. Although this task is omnipresent, little research has been conducted on the analysis and application of interrelations among given names from a data mining perspective. The present work tackles the problem of recommending given names, by firstly mining for inter-name relatedness in data from the Social Web. Based on these results, the name search engine "Nameling" was built, which attracted more than 35,000 users within less than six months, underpinning the relevance of the underlying recommendation task. The accruing usage data is then used for evaluating different state-of-the-art recommendation systems, as well our new \NR algorithm which we adopted from our previous work on folksonomies and which yields the best results, considering the trade-off between prediction accuracy and runtime performance as well as its ability to generate personalized recommendations. We also show, how the gathered inter-name relationships can be used for meaningful result diversification of PageRank-based recommendation systems. As all of the considered usage data is made publicly available, the present work establishes baseline results, encouraging other researchers to implement advanced recommendation systems for given names. - 1.Atzmueller, M., Kibanov, M., Scholz, C., Stumme, G.: {Conferator - a Social System for Conference and Contact Management}, (2013).
@misc{atzmueller2013conferator,
author = {Atzmueller, Martin and Kibanov, Mark and Scholz, Christoph and Stumme, Gerd},
howpublished = {Poster at INFORMATIK 2013},
institution = {University of Koblenz-Landau},
keywords = {itegpub},
publisher = {INFORMATIK 2013},
title = {{Conferator - a Social System for Conference and Contact Management}},
year = 2013
}%0 Generic
%1 atzmueller2013conferator
%A Atzmueller, Martin
%A Kibanov, Mark
%A Scholz, Christoph
%A Stumme, Gerd
%D 2013
%I INFORMATIK 2013
%T {Conferator - a Social System for Conference and Contact Management} - 1.Mobasher, B., Jannach, D., Geyer, W., Freyne, J., Hotho, A., Anand, S.S., Guy, I. eds.: Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013. CEUR-WS.org (2013).
@proceedings{conf/recsys/2013rsweb,
booktitle = {RSWeb@RecSys},
editor = {Mobasher, Bamshad and Jannach, Dietmar and Geyer, Werner and Freyne, Jill and Hotho, Andreas and Anand, Sarabjot Singh and Guy, Ido},
keywords = {bibsonomy},
publisher = {CEUR-WS.org},
series = {CEUR Workshop Proceedings},
title = {Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013.},
volume = 1066,
year = 2013
}%0 Conference Proceedings
%1 conf/recsys/2013rsweb
%B RSWeb@RecSys
%D 2013
%E Mobasher, Bamshad
%E Jannach, Dietmar
%E Geyer, Werner
%E Freyne, Jill
%E Hotho, Andreas
%E Anand, Sarabjot Singh
%E Guy, Ido
%I CEUR-WS.org
%T Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013.
%U http://ceur-ws.org/Vol-1066
%V 1066 - 1.Kluegl, P., Toepfer, M., Lemmerich, F., Hotho, A., Puppe, F.: Exploiting Structural Consistencies with Stacked Conditional Random Fields. Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics. 30, 111–125 (2013).Conditional Random Fields (CRF) are popular methods for labeling unstructured or textual data. Like many machine learning approaches, these undirected graphical models assume the instances to be independently distributed. However, in real-world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. We apply rule learning collectively on the predictions of an initial CRF for one context to acquire descriptions of its specific properties. Then, we utilize these descriptions as dynamic and high quality features in an additional (stacked) CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.
@article{kluegl2013exploiting,
abstract = {Conditional Random Fields (CRF) are popular methods for labeling unstructured or textual data. Like many machine learning approaches, these undirected graphical models assume the instances to be independently distributed. However, in real-world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. We apply rule learning collectively on the predictions of an initial CRF for one context to acquire descriptions of its specific properties. Then, we utilize these descriptions as dynamic and high quality features in an additional (stacked) CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.},
author = {Kluegl, Peter and Toepfer, Martin and Lemmerich, Florian and Hotho, Andreas and Puppe, Frank},
journal = {Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics},
keywords = {ie},
pages = {111-125},
title = {Exploiting Structural Consistencies with Stacked Conditional Random Fields},
volume = 30,
year = 2013
}%0 Journal Article
%1 kluegl2013exploiting
%A Kluegl, Peter
%A Toepfer, Martin
%A Lemmerich, Florian
%A Hotho, Andreas
%A Puppe, Frank
%D 2013
%J Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics
%P 111-125
%T Exploiting Structural Consistencies with Stacked Conditional Random Fields
%V 30
%X Conditional Random Fields (CRF) are popular methods for labeling unstructured or textual data. Like many machine learning approaches, these undirected graphical models assume the instances to be independently distributed. However, in real-world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. We apply rule learning collectively on the predictions of an initial CRF for one context to acquire descriptions of its specific properties. Then, we utilize these descriptions as dynamic and high quality features in an additional (stacked) CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error. - 1.Doerfel, S., Hotho, A., Kartal-Aydemir, A., Roßnagel, A., Stumme, G.: Informationelle Selbstbestimmung Im Web 2.0 Chancen Und Risiken Sozialer Verschlagwortungssysteme. Vieweg + Teubner Verlag (2013).
@book{doerfel2013informationelle,
author = {Doerfel, Stephan and Hotho, Andreas and Kartal-Aydemir, Aliye and Roßnagel, Alexander and Stumme, Gerd},
keywords = {itegpub},
publisher = {Vieweg + Teubner Verlag},
title = {Informationelle Selbstbestimmung Im Web 2.0 Chancen Und Risiken Sozialer Verschlagwortungssysteme},
year = 2013
}%0 Book
%1 doerfel2013informationelle
%A Doerfel, Stephan
%A Hotho, Andreas
%A Kartal-Aydemir, Aliye
%A Roßnagel, Alexander
%A Stumme, Gerd
%D 2013
%I Vieweg + Teubner Verlag
%T Informationelle Selbstbestimmung Im Web 2.0 Chancen Und Risiken Sozialer Verschlagwortungssysteme
%U http://www.worldcat.org/search?qt=worldcat_org_all&q=9783642380556
%@ 9783642380556 3642380557 - 1.Kibanov, M., Atzmueller, M., Scholz, C., Stumme, G.: On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity. In: Guerrero, J.E. (ed.) Proceedings of the 2013 IEEE Cyber, Physical and Social Computing, CPSCom 2013, Beijing, China, 20-23 August, 2013. pp. 993–1000. IEEE Computer Society, Los Alamitos, CA, USA (2013).Communities are a central aspect in the formation of social interaction networks. In this paper, we analyze the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific conferences. We compare the basic properties of the contact graphs to describe the properties of the contact networks and analyze the resulting community structure using state-of-the-art automic community detection algorithms. Specifically, we analyze the evolution of contacts and communities over time to consider the stability of the respective communities. In addition, we assess different factors which have an influence on the quality of community prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.
@inproceedings{kibanov2013evolution,
abstract = {Communities are a central aspect in the formation of social interaction networks. In this paper, we analyze the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific conferences. We compare the basic properties of the contact graphs to describe the properties of the contact networks and analyze the resulting community structure using state-of-the-art automic community detection algorithms. Specifically, we analyze the evolution of contacts and communities over time to consider the stability of the respective communities. In addition, we assess different factors which have an influence on the quality of community prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.},
address = {Los Alamitos, CA, USA},
author = {Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd},
booktitle = {Proceedings of the 2013 IEEE Cyber, Physical and Social Computing, CPSCom 2013, Beijing, China, 20-23 August, 2013},
editor = {Guerrero, Juan E.},
keywords = {itegpub},
pages = {993--1000},
publisher = {IEEE Computer Society},
title = {On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity},
year = 2013
}%0 Conference Paper
%1 kibanov2013evolution
%A Kibanov, Mark
%A Atzmueller, Martin
%A Scholz, Christoph
%A Stumme, Gerd
%B Proceedings of the 2013 IEEE Cyber, Physical and Social Computing, CPSCom 2013, Beijing, China, 20-23 August, 2013
%C Los Alamitos, CA, USA
%D 2013
%E Guerrero, Juan E.
%I IEEE Computer Society
%P 993--1000
%T On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity
%U http://dx.doi.org/10.1109/GreenCom-iThings-CPSCom.2013.170
%X Communities are a central aspect in the formation of social interaction networks. In this paper, we analyze the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific conferences. We compare the basic properties of the contact graphs to describe the properties of the contact networks and analyze the resulting community structure using state-of-the-art automic community detection algorithms. Specifically, we analyze the evolution of contacts and communities over time to consider the stability of the respective communities. In addition, we assess different factors which have an influence on the quality of community prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks. - 1.Mitzlaff, F., Atzmueller, M., Stumme, G., Hotho, A.: {Semantics of User Interaction in Social Media}. In: Ghoshal, G., Poncela-Casasnovas, J., and Tolksdorf, R. (eds.) Complex Networks IV. Springer Verlag, Heidelberg, Germany (2013). https://doi.org/10.1007/978-3-642-36844-8_2.
@incollection{mitzlaff2013semantics,
address = {Heidelberg, Germany},
author = {Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas},
booktitle = {Complex Networks IV},
editor = {Ghoshal, Gourab and Poncela-Casasnovas, Julia and Tolksdorf, Robert},
keywords = {itegpub},
publisher = {Springer Verlag},
series = {Studies in Computational Intelligence},
title = {{Semantics of User Interaction in Social Media}},
volume = 476,
year = 2013
}%0 Book Section
%1 mitzlaff2013semantics
%A Mitzlaff, Folke
%A Atzmueller, Martin
%A Stumme, Gerd
%A Hotho, Andreas
%B Complex Networks IV
%C Heidelberg, Germany
%D 2013
%E Ghoshal, Gourab
%E Poncela-Casasnovas, Julia
%E Tolksdorf, Robert
%I Springer Verlag
%R 10.1007/978-3-642-36844-8_2
%T {Semantics of User Interaction in Social Media}
%V 476 - 1.Scholz, C., Atzmueller, M., Kibanov, M., Stumme, G.: How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks. In: Rokne, J.G. and Faloutsos, C. (eds.) Proceedings of the 2013 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, Niagara Falls, Canada, August 25-28, 2013. pp. 356–363. ACM, New York, NY, USA (2013).Understanding the process of link creation is rather important for link prediction in social networks. Therefore, this paper analyzes contact structures in networks of face-to-face spatial proximity, and presents new insights on the dynamic and static contact behavior in such real world networks. We focus on face-to-face contact networks collected at different conferences using the social conference guidance system Conferator. Specifically, we investigate the strength of ties and its connection to triadic closures in face-to-face proximity networks. Furthermore, we analyze the predictability of all, new and recurring links at different points of time during the conference. In addition, we consider network dynamics for the prediction of new links.
@inproceedings{scholz2013people,
abstract = {Understanding the process of link creation is rather important for link prediction in social networks. Therefore, this paper analyzes contact structures in networks of face-to-face spatial proximity, and presents new insights on the dynamic and static contact behavior in such real world networks. We focus on face-to-face contact networks collected at different conferences using the social conference guidance system Conferator. Specifically, we investigate the strength of ties and its connection to triadic closures in face-to-face proximity networks. Furthermore, we analyze the predictability of all, new and recurring links at different points of time during the conference. In addition, we consider network dynamics for the prediction of new links.},
address = {New York, NY, USA},
author = {Scholz, Christoph and Atzmueller, Martin and Kibanov, Mark and Stumme, Gerd},
booktitle = {Proceedings of the 2013 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, Niagara Falls, Canada, August 25-28, 2013},
editor = {Rokne, Jon G. and Faloutsos, Christos},
keywords = {network},
pages = {356--363},
publisher = {ACM},
title = {How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks},
year = 2013
}%0 Conference Paper
%1 scholz2013people
%A Scholz, Christoph
%A Atzmueller, Martin
%A Kibanov, Mark
%A Stumme, Gerd
%B Proceedings of the 2013 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, Niagara Falls, Canada, August 25-28, 2013
%C New York, NY, USA
%D 2013
%E Rokne, Jon G.
%E Faloutsos, Christos
%I ACM
%P 356--363
%T How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks
%U http://dx.doi.org/10.1145/2492517.2492521
%X Understanding the process of link creation is rather important for link prediction in social networks. Therefore, this paper analyzes contact structures in networks of face-to-face spatial proximity, and presents new insights on the dynamic and static contact behavior in such real world networks. We focus on face-to-face contact networks collected at different conferences using the social conference guidance system Conferator. Specifically, we investigate the strength of ties and its connection to triadic closures in face-to-face proximity networks. Furthermore, we analyze the predictability of all, new and recurring links at different points of time during the conference. In addition, we consider network dynamics for the prediction of new links. - 1.Mitzlaff, F., Atzmueller, M., Stumme, G., Hotho, A.: {On the Semantics of User Interaction in Social Media (Extended Abstract)}. In: Proc. LWA 2013 (KDML Special Track). University of Bamberg, Bamberg, Germany (2013).
@inproceedings{MASH:13b,
address = {Bamberg, Germany},
author = {Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas},
booktitle = {Proc. LWA 2013 (KDML Special Track)},
keywords = {itegpub},
publisher = {University of Bamberg},
title = {{On the Semantics of User Interaction in Social Media (Extended Abstract)}},
year = 2013
}%0 Conference Paper
%1 MASH:13b
%A Mitzlaff, Folke
%A Atzmueller, Martin
%A Stumme, Gerd
%A Hotho, Andreas
%B Proc. LWA 2013 (KDML Special Track)
%C Bamberg, Germany
%D 2013
%I University of Bamberg
%T {On the Semantics of User Interaction in Social Media (Extended Abstract)}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2013-lwa-kdml-user-semantics-social-media-extended-abstract.pdf - 1.Kibanov, M., Atzmueller, M., Scholz, C., Stumme, G.: {Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract, Resubmission)}. In: Proc. LWA 2013 (KDML Special Track). University of Bamberg, Bamberg, Germany (2013).
@inproceedings{KASS:13b,
address = {Bamberg, Germany},
author = {Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd},
booktitle = {Proc. LWA 2013 (KDML Special Track)},
keywords = {contacts},
publisher = {University of Bamberg},
title = {{Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract, Resubmission)}},
year = 2013
}%0 Conference Paper
%1 KASS:13b
%A Kibanov, Mark
%A Atzmueller, Martin
%A Scholz, Christoph
%A Stumme, Gerd
%B Proc. LWA 2013 (KDML Special Track)
%C Bamberg, Germany
%D 2013
%I University of Bamberg
%T {Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract, Resubmission)} - 1.Mitzlaff, F., Stumme, G.: Onomastics 2.0 - The Power of Social Co-Occurrences, http://arxiv.org/abs/1303.0484, (2013).Onomastics is "the science or study of the origin and forms of proper names of persons or places." ["Onomastics". Merriam-Webster.com, 2013. http://www.merriam-webster.com (11 February 2013)]. Especially personal names play an important role in daily life, as all over the world future parents are facing the task of finding a suitable given name for their child. This choice is influenced by different factors, such as the social context, language, cultural background and, in particular, personal taste. With the rise of the Social Web and its applications, users more and more interact digitally and participate in the creation of heterogeneous, distributed, collaborative data collections. These sources of data also reflect current and new naming trends as well as new emerging interrelations among names. The present work shows, how basic approaches from the field of social network analysis and information retrieval can be applied for discovering relations among names, thus extending Onomastics by data mining techniques. The considered approach starts with building co-occurrence graphs relative to data from the Social Web, respectively for given names and city names. As a main result, correlations between semantically grounded similarities among names (e.g., geographical distance for city names) and structural graph based similarities are observed. The discovered relations among given names are the foundation of "nameling" [http://nameling.net], a search engine and academic research platform for given names which attracted more than 30,000 users within four months, underpinningthe relevance of the proposed methodology.
@misc{mitzlaff2013onomastics,
abstract = {Onomastics is "the science or study of the origin and forms of proper names of persons or places." ["Onomastics". Merriam-Webster.com, 2013. http://www.merriam-webster.com (11 February 2013)]. Especially personal names play an important role in daily life, as all over the world future parents are facing the task of finding a suitable given name for their child. This choice is influenced by different factors, such as the social context, language, cultural background and, in particular, personal taste. With the rise of the Social Web and its applications, users more and more interact digitally and participate in the creation of heterogeneous, distributed, collaborative data collections. These sources of data also reflect current and new naming trends as well as new emerging interrelations among names. The present work shows, how basic approaches from the field of social network analysis and information retrieval can be applied for discovering relations among names, thus extending Onomastics by data mining techniques. The considered approach starts with building co-occurrence graphs relative to data from the Social Web, respectively for given names and city names. As a main result, correlations between semantically grounded similarities among names (e.g., geographical distance for city names) and structural graph based similarities are observed. The discovered relations among given names are the foundation of "nameling" [http://nameling.net], a search engine and academic research platform for given names which attracted more than 30,000 users within four months, underpinningthe relevance of the proposed methodology.},
author = {Mitzlaff, Folke and Stumme, Gerd},
keywords = {nameling},
note = {cite arxiv:1303.0484Comment: Historically, this is the first paper on the analysis of names in the context of the name search engine 'nameling'. arXiv admin note: text overlap with arXiv:1302.4412},
title = {Onomastics 2.0 - The Power of Social Co-Occurrences},
year = 2013
}%0 Generic
%1 mitzlaff2013onomastics
%A Mitzlaff, Folke
%A Stumme, Gerd
%D 2013
%T Onomastics 2.0 - The Power of Social Co-Occurrences
%U http://arxiv.org/abs/1303.0484
%X Onomastics is "the science or study of the origin and forms of proper names of persons or places." ["Onomastics". Merriam-Webster.com, 2013. http://www.merriam-webster.com (11 February 2013)]. Especially personal names play an important role in daily life, as all over the world future parents are facing the task of finding a suitable given name for their child. This choice is influenced by different factors, such as the social context, language, cultural background and, in particular, personal taste. With the rise of the Social Web and its applications, users more and more interact digitally and participate in the creation of heterogeneous, distributed, collaborative data collections. These sources of data also reflect current and new naming trends as well as new emerging interrelations among names. The present work shows, how basic approaches from the field of social network analysis and information retrieval can be applied for discovering relations among names, thus extending Onomastics by data mining techniques. The considered approach starts with building co-occurrence graphs relative to data from the Social Web, respectively for given names and city names. As a main result, correlations between semantically grounded similarities among names (e.g., geographical distance for city names) and structural graph based similarities are observed. The discovered relations among given names are the foundation of "nameling" [http://nameling.net], a search engine and academic research platform for given names which attracted more than 30,000 users within four months, underpinningthe relevance of the proposed methodology. - 1.Atzmueller, M., Bobek, S., Kibanov, M., Nalepa, G.J.: Towards the Ambient Classroom: An Environment for Enhancing Collaborative Educational Processes. In: Roth-Berghofer, T., Oussena, S., and Atzmueller, M. (eds.) Proceedings of the Smart University Workshop, SmartUni 2013 -- International and Interdisciplinary Conference on Modeling and Using Context, Context 2013, Annecy, Haute-Savoie, France, 28 October, 2013 (2013).With the rapid development of mobile technologies like, e.g., RFID tags, smartphones, and tablets, ambient intelligence applications have gained a huge popularity in recent years. However, most of the existing approaches aim at developing ambient environments that are rather static, and do not take the aspect of social interaction between the inhabitants into account. We argue that this is essential for smart classrooms, meeting rooms and other environments that are strictly based on mechanisms of human face-to-face interactions. In the context of the smart university, we propose the ambient classroom system for enhancing collaborative educational processes using sensor fusion, data mining, semantic technologies, and inference methods.
@inproceedings{atzmueller2013towards,
abstract = {With the rapid development of mobile technologies like, e.g., RFID tags, smartphones, and tablets, ambient intelligence applications have gained a huge popularity in recent years. However, most of the existing approaches aim at developing ambient environments that are rather static, and do not take the aspect of social interaction between the inhabitants into account. We argue that this is essential for smart classrooms, meeting rooms and other environments that are strictly based on mechanisms of human face-to-face interactions. In the context of the smart university, we propose the ambient classroom system for enhancing collaborative educational processes using sensor fusion, data mining, semantic technologies, and inference methods.},
author = {Atzmueller, Martin and Bobek, Szymon and Kibanov, Mark and Nalepa, Grzegorz J.},
booktitle = {Proceedings of the Smart University Workshop, SmartUni 2013 -- International and Interdisciplinary Conference on Modeling and Using Context, Context 2013, Annecy, Haute-Savoie, France, 28 October, 2013},
editor = {Roth-Berghofer, Thomas and Oussena, Samia and Atzmueller, Martin},
keywords = 2013,
title = {Towards the Ambient Classroom: An Environment for Enhancing Collaborative Educational Processes},
year = 2013
}%0 Conference Paper
%1 atzmueller2013towards
%A Atzmueller, Martin
%A Bobek, Szymon
%A Kibanov, Mark
%A Nalepa, Grzegorz J.
%B Proceedings of the Smart University Workshop, SmartUni 2013 -- International and Interdisciplinary Conference on Modeling and Using Context, Context 2013, Annecy, Haute-Savoie, France, 28 October, 2013
%D 2013
%E Roth-Berghofer, Thomas
%E Oussena, Samia
%E Atzmueller, Martin
%T Towards the Ambient Classroom: An Environment for Enhancing Collaborative Educational Processes
%U http://www.univ-savoie.org/context2013/SmartUni2013.pdf
%X With the rapid development of mobile technologies like, e.g., RFID tags, smartphones, and tablets, ambient intelligence applications have gained a huge popularity in recent years. However, most of the existing approaches aim at developing ambient environments that are rather static, and do not take the aspect of social interaction between the inhabitants into account. We argue that this is essential for smart classrooms, meeting rooms and other environments that are strictly based on mechanisms of human face-to-face interactions. In the context of the smart university, we propose the ambient classroom system for enhancing collaborative educational processes using sensor fusion, data mining, semantic technologies, and inference methods. - 1.Mitzlaff, F., Atzmueller, M., Benz, D., Hotho, A., Stumme, G.: User-Relatedness and Community Structure in Social Interaction Networks, http://arxiv.org/abs/1309.3888, (2013).With social media and the according social and ubiquitous applications finding their way into everyday life, there is a rapidly growing amount of user generated content yielding explicit and implicit network structures. We consider social activities and phenomena as proxies for user relatedness. Such activities are represented in so-called social interaction networks or evidence networks, with different degrees of explicitness. We focus on evidence networks containing relations on users, which are represented by connections between individual nodes. Explicit interaction networks are then created by specific user actions, for example, when building a friend network. On the other hand, more implicit networks capture user traces or evidences of user actions as observed in Web portals, blogs, resource sharing systems, and many other social services. These implicit networks can be applied for a broad range of analysis methods instead of using expensive gold-standard information. In this paper, we analyze different properties of a set of networks in social media. We show that there are dependencies and correlations between the networks. These allow for drawing reciprocal conclusions concerning pairs of networks, based on the assessment of structural correlations and ranking interchangeability. Additionally, we show how these inter-network correlations can be used for assessing the results of structural analysis techniques, e.g., community mining methods.
@misc{mitzlaff2013userrelatedness,
abstract = {With social media and the according social and ubiquitous applications finding their way into everyday life, there is a rapidly growing amount of user generated content yielding explicit and implicit network structures. We consider social activities and phenomena as proxies for user relatedness. Such activities are represented in so-called social interaction networks or evidence networks, with different degrees of explicitness. We focus on evidence networks containing relations on users, which are represented by connections between individual nodes. Explicit interaction networks are then created by specific user actions, for example, when building a friend network. On the other hand, more implicit networks capture user traces or evidences of user actions as observed in Web portals, blogs, resource sharing systems, and many other social services. These implicit networks can be applied for a broad range of analysis methods instead of using expensive gold-standard information. In this paper, we analyze different properties of a set of networks in social media. We show that there are dependencies and correlations between the networks. These allow for drawing reciprocal conclusions concerning pairs of networks, based on the assessment of structural correlations and ranking interchangeability. Additionally, we show how these inter-network correlations can be used for assessing the results of structural analysis techniques, e.g., community mining methods.},
author = {Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
keywords = {networks},
note = {cite arxiv:1309.3888},
title = {User-Relatedness and Community Structure in Social Interaction Networks},
year = 2013
}%0 Generic
%1 mitzlaff2013userrelatedness
%A Mitzlaff, Folke
%A Atzmueller, Martin
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%D 2013
%T User-Relatedness and Community Structure in Social Interaction Networks
%U http://arxiv.org/abs/1309.3888
%X With social media and the according social and ubiquitous applications finding their way into everyday life, there is a rapidly growing amount of user generated content yielding explicit and implicit network structures. We consider social activities and phenomena as proxies for user relatedness. Such activities are represented in so-called social interaction networks or evidence networks, with different degrees of explicitness. We focus on evidence networks containing relations on users, which are represented by connections between individual nodes. Explicit interaction networks are then created by specific user actions, for example, when building a friend network. On the other hand, more implicit networks capture user traces or evidences of user actions as observed in Web portals, blogs, resource sharing systems, and many other social services. These implicit networks can be applied for a broad range of analysis methods instead of using expensive gold-standard information. In this paper, we analyze different properties of a set of networks in social media. We show that there are dependencies and correlations between the networks. These allow for drawing reciprocal conclusions concerning pairs of networks, based on the assessment of structural correlations and ranking interchangeability. Additionally, we show how these inter-network correlations can be used for assessing the results of structural analysis techniques, e.g., community mining methods. - 1.Roth-Berghofer, T., Oussena, S., Atzmueller, M. eds.: {Proceedings of the 2013 International Smart University Workshop (SmartU 2013)}. CONTEXT 2013, Annecy, France (2013).
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%T {Proceedings of the 2013 International Smart University Workshop (SmartU 2013)} - 1.Atzmueller, M., Hilgenberg, K.: {SDCF - A Sensor Data Collection Framework for Social and Ubiquitous Environments: Challenges and First Experiences in Sensor-based Social Networks (Abstract)}. In: Proc. Sunbelt XXXIII: Annual Meeting of the International Network for Social Network Analysis. INSNA, Hamburg, Germany (2013).
@inproceedings{AH:13a,
address = {Hamburg, Germany},
author = {Atzmueller, Martin and Hilgenberg, Katy},
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%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2013-Atzmueller-SDCF-Sunbelt-ExtendedAbstract.pdf - 1.Atzmueller, M., Hilgenberg, K.: {Towards Capturing Social Interactions with SDCF: An Extensible Framework for Mobile Sensing and Ubiquitous Data Collection}. In: Proc. 4th International Workshop on Modeling Social Media (MSM 2013), Hypertext 2013. ACM Press, New York, NY, USA (2013).
@inproceedings{AH:13b,
address = {New York, NY, USA},
author = {Atzmueller, Martin and Hilgenberg, Katy},
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title = {{Towards Capturing Social Interactions with SDCF: An Extensible Framework for Mobile Sensing and Ubiquitous Data Collection}},
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%D 2013
%I ACM Press
%T {Towards Capturing Social Interactions with SDCF: An Extensible Framework for Mobile Sensing and Ubiquitous Data Collection} - 1.Atzmueller, M., Lemmerich, F.: {Exploratory Pattern Mining on Social Media using Geo-References and Social Tagging Information}. International Journal of Web Science. 2, (2013).
@article{AL:13,
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%V 2 - 1.Atzmueller, M., Chin, A., Helic, D., Hotho, A. eds.: {Ubiquitous Social Media Analysis}. Springer Verlag, Heidelberg, Germany (2013).
@proceedings{ACHH:13,
address = {Heidelberg, Germany},
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editor = {Atzmueller, Martin and Chin, Alvin and Helic, Denis and Hotho, Andreas},
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%V 8329 - 1.Macek, B.-E., Atzmueller, M.: Visualizing The Impact of Time Series Data for Predicting User Interactions. In: Proc. ASONAM 2013. ACM Press, New York, NY, USA (2013).
@conference{MA:13a,
address = {New York, NY, USA},
author = {Macek, Björn-Elmar and Atzmueller, Martin},
booktitle = {Proc. ASONAM 2013},
keywords = {itegpub},
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title = {Visualizing The Impact of Time Series Data for Predicting User Interactions},
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%T Visualizing The Impact of Time Series Data for Predicting User Interactions - 1.Singer, P., Niebler, T., Strohmaier, M., Hotho, A.: Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia. International Journal on Semantic Web and Information Systems (IJSWIS). 9, 41–70 (2013). https://doi.org/10.4018/ijswis.2013100103.In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.
@article{singer2013computing,
abstract = {In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.},
author = {Singer, Philipp and Niebler, Thomas and Strohmaier, Markus and Hotho, Andreas},
journal = {International Journal on Semantic Web and Information Systems (IJSWIS)},
keywords = 2013,
number = 4,
pages = {41--70},
publisher = {IGI Global},
title = {Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia},
volume = 9,
year = 2013
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%N 4
%P 41--70
%R 10.4018/ijswis.2013100103
%T Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia
%U http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijswis.2013100103
%V 9
%X In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia’s content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment – a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors’ results are intriguing: They suggest that (i) semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia’s plain link structure alone and (ii) that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors’ work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task. - 1.Schulz, T., Skistims, H., Zirfas, J., Atzmueller, M., Scholz, C.: {Rechtliche Ausgestaltung sozialer Konferenzplattformen}. ZD. 2, 60–65 (2013).
@article{SSZAS:13,
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keywords = {recht},
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title = {{Rechtliche Ausgestaltung sozialer Konferenzplattformen}},
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%T {Rechtliche Ausgestaltung sozialer Konferenzplattformen}
%V 2 - 1.Atzmueller, M., Mueller, J.: {Subgroup Analytics and Interactive Assessment on Ubiquitous Data}. In: {Proceedings of the International Workshop on Mining Ubiquitous and Social Environments (MUSE2013)}. , Prague, Czech Republic (2013).
@inproceedings{AM:13,
address = {Prague, Czech Republic},
author = {Atzmueller, Martin and Mueller, Juergen},
booktitle = {{Proceedings of the International Workshop on Mining Ubiquitous and Social Environments (MUSE2013)}},
keywords = {itegpub},
title = {{Subgroup Analytics and Interactive Assessment on Ubiquitous Data}},
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}%0 Conference Paper
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%T {Subgroup Analytics and Interactive Assessment on Ubiquitous Data} - 1.Kibanov, M., Atzmueller, M., Scholz, C., Stumme, G.: {Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract)}. In: Proc. LWA 2013 (KDML Special Track). University of Bamberg, Bamberg, Germany (2013).
@inproceedings{KASS:13b,
address = {Bamberg, Germany},
author = {Kibanov, Mark and Atzmueller, Martin and Scholz, Christoph and Stumme, Gerd},
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title = {{Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract)}},
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%D 2013
%I University of Bamberg
%T {Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract)}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2013-lwa-kdml-community-evolution-extended-abstract.pdf - 1.Seipel, D., Köhler, S., Neubeck, P., Atzmueller, M.: {Mining Complex Event Patterns in Computer Networks}. In: {Postproceedings of the 1st Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2012}. Springer Verlag, Heidelberg, Germany (2013).
@incollection{SKNA:13,
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%T {Mining Complex Event Patterns in Computer Networks} - 1.Scholz, {Christoph, Atzmueller, M., Barrat, A., Cattuto, C., Gerd Stumme}: {New Insights and Methods For Predicting Face-To-Face Contacts}. In: Proc. 7th Intl. AAAI Conference on Weblogs and Social Media. AAAI Press, Palo Alto, CA, USA (2013).
@inproceedings{christophscholzandmartinatzmuellerandalainbarratandcirocattutoandgerdstumme2013insights,
address = {Palo Alto, CA, USA},
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%T {New Insights and Methods For Predicting Face-To-Face Contacts} - 1.Atzmueller, M., Scholz, C. eds.: {Proceedings of the 2013 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2013)}. ECML/PKDD 2013, Prague, Czech Republic (2013).
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@inproceedings{SABCS:13,
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author = {Scholz, Christoph and Atzmueller, Martin and Barrat, Alain and Cattuto, Ciro and Stumme, Gerd},
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%C Palo Alto, CA, USA
%D 2013
%I AAAI Press
%T New Insights and Methods For Predicting Face-To-Face Contacts - 1.Atzmueller, M.: {Community and Pattern Analytics in Social Networks}, https://www.kde.cs.uni-kassel.de/atzmueller/paper/2013-atzmueller-lwa13-abstract.pdf, (2013).
@misc{Atzmueller:13:LWA13:Tutorial,
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editor = {2013, LWA},
howpublished = {Tutorial Abstract},
keywords = {itegpub},
title = {{Community and Pattern Analytics in Social Networks}},
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%E 2013, LWA
%T {Community and Pattern Analytics in Social Networks}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2013-atzmueller-lwa13-abstract.pdf - 1.Atzmueller, M.: {Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities}. In: Chin, A. and Zhang, D. (eds.) Mobile Social Networking: An Innovative Approach. Springer Verlag, Heidelberg, Germany (2013).
@incollection{Atzmueller:13,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin},
booktitle = {Mobile Social Networking: An Innovative Approach},
editor = {Chin, Alvin and Zhang, Daqing},
keywords = {itegpub},
publisher = {Springer Verlag},
title = {{Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities}},
year = 2013
}%0 Book Section
%1 Atzmueller:13
%A Atzmueller, Martin
%B Mobile Social Networking: An Innovative Approach
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%E Chin, Alvin
%E Zhang, Daqing
%I Springer Verlag
%T {Social Behavior in Mobile Social Networks: Characterizing Links, Roles and Communities} - 1.Doerfel, S., Jäschke, R.: An analysis of tag-recommender evaluation procedures. In: Proceedings of the 7th ACM conference on Recommender systems. pp. 343–346. ACM, Hong Kong, China (2013). https://doi.org/10.1145/2507157.2507222.Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.
@inproceedings{doerfel2013analysis,
abstract = {Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.},
address = {New York, NY, USA},
author = {Doerfel, Stephan and Jäschke, Robert},
booktitle = {Proceedings of the 7th ACM conference on Recommender systems},
keywords = {bookmarking},
pages = {343--346},
publisher = {ACM},
series = {RecSys '13},
title = {An analysis of tag-recommender evaluation procedures},
year = 2013
}%0 Conference Paper
%1 doerfel2013analysis
%A Doerfel, Stephan
%A Jäschke, Robert
%B Proceedings of the 7th ACM conference on Recommender systems
%C New York, NY, USA
%D 2013
%I ACM
%P 343--346
%R 10.1145/2507157.2507222
%T An analysis of tag-recommender evaluation procedures
%U https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2013analysis.pdf
%X Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.
%@ 978-1-4503-2409-0 - 1.Kibanov, M., Erdmann, D.J., Atzmueller, M.: {How to Select a Suitable Tool for a Software Development Project: Three Case Studies and the Lessons Learned}. In: Software Engineering 2013 - Workshopband. Gesellschaft für Informatik (2013).
@inproceedings{KEA:13,
author = {Kibanov, Mark and Erdmann, Dominik J. and Atzmueller, Martin},
booktitle = {Software Engineering 2013 - Workshopband},
keywords = {itegpub},
publisher = {Gesellschaft für Informatik},
title = {{How to Select a Suitable Tool for a Software Development Project: Three Case Studies and the Lessons Learned}},
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}%0 Conference Paper
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%A Erdmann, Dominik J.
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%I Gesellschaft für Informatik
%T {How to Select a Suitable Tool for a Software Development Project: Three Case Studies and the Lessons Learned}
2012
- 1.Atzmueller, M., Beer, S., Puppe, F.: {Data Mining, Validation and Collaborative Knowledge Capture}. In: Brüggemann, S. and d’Amato, C. (eds.) Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources. pp. 149–167. IGI Global (2012).
@incollection{ABP:11,
author = {Atzmueller, Martin and Beer, Stephanie and Puppe, Frank},
booktitle = {Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources},
editor = {Brüggemann, Stefan and d’Amato, Claudia},
keywords = {itegpub},
pages = {149-167},
publisher = {IGI Global},
title = {{Data Mining, Validation and Collaborative Knowledge Capture}},
year = 2012
}%0 Book Section
%1 ABP:11
%A Atzmueller, Martin
%A Beer, Stephanie
%A Puppe, Frank
%B Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources
%D 2012
%E Brüggemann, Stefan
%E d’Amato, Claudia
%I IGI Global
%P 149-167
%T {Data Mining, Validation and Collaborative Knowledge Capture} - 1.Atzmueller, M., Becker, M., Doerfel, S., Kibanov, M., Hotho, A., Macek, B.-E., Mitzlaff, F., Mueller, J., Scholz, C., Stumme, G.: Ubicon: Observing Social and Physical Activities. In: Proceedings of the 2012 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012. pp. 317–324. IEEE Computer Society, Los Alamitos, CA, USA (2012).The connection of ubiquitous and social computing is an emerging research area which is combining two prominent areas of computer science. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. Furthermore, we give an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous and social applications for diverse tasks and projects. Ubicon features the collection and analysis of both physical and social activities of users for enabling inter-connected applications in ubiquitous and social contexts. We summarize three real-world systems built on top of Ubicon, and exemplarily discuss the according mining and analysis aspects.
@inproceedings{ABDHKMMMSS:12,
abstract = {The connection of ubiquitous and social computing is an emerging research area which is combining two prominent areas of computer science. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. Furthermore, we give an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous and social applications for diverse tasks and projects. Ubicon features the collection and analysis of both physical and social activities of users for enabling inter-connected applications in ubiquitous and social contexts. We summarize three real-world systems built on top of Ubicon, and exemplarily discuss the according mining and analysis aspects.},
address = {Los Alamitos, CA, USA},
author = {Atzmueller, Martin and Becker, Martin and Doerfel, Stephan and Kibanov, Mark and Hotho, Andreas and Macek, Björn-Elmar and Mitzlaff, Folke and Mueller, Juergen and Scholz, Christoph and Stumme, Gerd},
booktitle = {Proceedings of the 2012 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012},
keywords = 2012,
month = 11,
pages = {317-324},
publisher = {IEEE Computer Society},
title = {Ubicon: Observing Social and Physical Activities},
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}%0 Conference Paper
%1 ABDHKMMMSS:12
%A Atzmueller, Martin
%A Becker, Martin
%A Doerfel, Stephan
%A Kibanov, Mark
%A Hotho, Andreas
%A Macek, Björn-Elmar
%A Mitzlaff, Folke
%A Mueller, Juergen
%A Scholz, Christoph
%A Stumme, Gerd
%B Proceedings of the 2012 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012
%C Los Alamitos, CA, USA
%D 2012
%I IEEE Computer Society
%P 317-324
%T Ubicon: Observing Social and Physical Activities
%U http://dx.doi.org/10.1109/GreenCom.2012.75
%X The connection of ubiquitous and social computing is an emerging research area which is combining two prominent areas of computer science. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. Furthermore, we give an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous and social applications for diverse tasks and projects. Ubicon features the collection and analysis of both physical and social activities of users for enabling inter-connected applications in ubiquitous and social contexts. We summarize three real-world systems built on top of Ubicon, and exemplarily discuss the according mining and analysis aspects. - 1.Strohmaier, M., Helic, D., Benz, D., Körner, C., Kern, R.: Evaluation of Folksonomy Induction Algorithms. Transactions on Intelligent Systems and Technology. (2012).
@article{strohmaier2011evaluation,
author = {Strohmaier, Markus and Helic, Denis and Benz, Dominik and Körner, Christian and Kern, Roman},
journal = {Transactions on Intelligent Systems and Technology},
keywords = 2012,
title = {Evaluation of Folksonomy Induction Algorithms},
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}%0 Journal Article
%1 strohmaier2011evaluation
%A Strohmaier, Markus
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%A Benz, Dominik
%A Körner, Christian
%A Kern, Roman
%D 2012
%J Transactions on Intelligent Systems and Technology
%T Evaluation of Folksonomy Induction Algorithms
%U http://tist.acm.org/index.html - 1.Doerfel, S., Jäschke, R., Hotho, A., Stumme, G.: Leveraging Publication Metadata and Social Data into FolkRank for Scientific Publication Recommendation. In: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web. pp. 9–16. ACM, Dublin, Ireland (2012). https://doi.org/10.1145/2365934.2365937.The ever-growing flood of new scientific articles requires novel retrieval mechanisms. One means for mitigating this instance of the information overload phenomenon are collaborative tagging systems, that allow users to select, share and annotate references to publications. These systems employ recommendation algorithms to present to their users personalized lists of interesting and relevant publications. In this paper we analyze different ways to incorporate social data and metadata from collaborative tagging systems into the graph-based ranking algorithm FolkRank to utilize it for recommending scientific articles to users of the social bookmarking system BibSonomy. We compare the results to those of Collaborative Filtering, which has previously been applied for resource recommendation.
@inproceedings{doerfel2012leveraging,
abstract = {The ever-growing flood of new scientific articles requires novel retrieval mechanisms. One means for mitigating this instance of the information overload phenomenon are collaborative tagging systems, that allow users to select, share and annotate references to publications. These systems employ recommendation algorithms to present to their users personalized lists of interesting and relevant publications. In this paper we analyze different ways to incorporate social data and metadata from collaborative tagging systems into the graph-based ranking algorithm FolkRank to utilize it for recommending scientific articles to users of the social bookmarking system BibSonomy. We compare the results to those of Collaborative Filtering, which has previously been applied for resource recommendation.},
address = {New York, NY, USA},
author = {Doerfel, Stephan and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web},
keywords = {bookmarking},
month = {09},
pages = {9--16},
publisher = {ACM},
title = {Leveraging Publication Metadata and Social Data into FolkRank for Scientific Publication Recommendation},
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}%0 Conference Paper
%1 doerfel2012leveraging
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%A Jäschke, Robert
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%C New York, NY, USA
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%I ACM
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%R 10.1145/2365934.2365937
%T Leveraging Publication Metadata and Social Data into FolkRank for Scientific Publication Recommendation
%U http://doi.acm.org/10.1145/2365934.2365937
%X The ever-growing flood of new scientific articles requires novel retrieval mechanisms. One means for mitigating this instance of the information overload phenomenon are collaborative tagging systems, that allow users to select, share and annotate references to publications. These systems employ recommendation algorithms to present to their users personalized lists of interesting and relevant publications. In this paper we analyze different ways to incorporate social data and metadata from collaborative tagging systems into the graph-based ranking algorithm FolkRank to utilize it for recommending scientific articles to users of the social bookmarking system BibSonomy. We compare the results to those of Collaborative Filtering, which has previously been applied for resource recommendation.
%@ 978-1-4503-1638-5 - 1.Landia, N., Anand, S.S., Hotho, A., Jäschke, R., Doerfel, S., Mitzlaff, F.: Extending FolkRank with Content Data. In: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web. pp. 1–8. ACM, Dublin, Ireland (2012). https://doi.org/10.1145/2365934.2365936.Real-world tagging datasets have a large proportion of new/ untagged documents. Few approaches for recommending tags to a user for a document address this new item problem, concentrating instead on artificially created post-core datasets where it is guaranteed that the user as well as the document of each test post is known to the system and already has some tags assigned to it. In order to recommend tags for new documents, approaches are required which model documents not only based on the tags assigned to them in the past (if any), but also the content. In this paper we present a novel adaptation to the widely recognised FolkRank tag recommendation algorithm by including content data. We adapt the FolkRank graph to use word nodes instead of document nodes, enabling it to recommend tags for new documents based on their textual content. Our adaptations make FolkRank applicable to post-core 1 ie. the full real-world tagging datasets and address the new item problem in tag recommendation. For comparison, we also apply and evaluate the same methodology of including content on a simpler tag recommendation algorithm. This results in a less expensive recommender which suggests a combination of user related and document content related tags. Including content data into FolkRank shows an improvement over plain FolkRank on full tagging datasets. However, we also observe that our simpler content-aware tag recommender outperforms FolkRank with content data. Our results suggest that an optimisation of the weighting method of FolkRank is required to achieve better results.
@inproceedings{landia2012extending,
abstract = {Real-world tagging datasets have a large proportion of new/ untagged documents. Few approaches for recommending tags to a user for a document address this new item problem, concentrating instead on artificially created post-core datasets where it is guaranteed that the user as well as the document of each test post is known to the system and already has some tags assigned to it. In order to recommend tags for new documents, approaches are required which model documents not only based on the tags assigned to them in the past (if any), but also the content. In this paper we present a novel adaptation to the widely recognised FolkRank tag recommendation algorithm by including content data. We adapt the FolkRank graph to use word nodes instead of document nodes, enabling it to recommend tags for new documents based on their textual content. Our adaptations make FolkRank applicable to post-core 1 ie. the full real-world tagging datasets and address the new item problem in tag recommendation. For comparison, we also apply and evaluate the same methodology of including content on a simpler tag recommendation algorithm. This results in a less expensive recommender which suggests a combination of user related and document content related tags. Including content data into FolkRank shows an improvement over plain FolkRank on full tagging datasets. However, we also observe that our simpler content-aware tag recommender outperforms FolkRank with content data. Our results suggest that an optimisation of the weighting method of FolkRank is required to achieve better results.},
address = {New York, NY, USA},
author = {Landia, Nikolas and Anand, Sarabjot Singh and Hotho, Andreas and Jäschke, Robert and Doerfel, Stephan and Mitzlaff, Folke},
booktitle = {Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web},
keywords = {bookmarking},
month = {09},
pages = {1--8},
publisher = {ACM},
title = {Extending FolkRank with Content Data},
year = 2012
}%0 Conference Paper
%1 landia2012extending
%A Landia, Nikolas
%A Anand, Sarabjot Singh
%A Hotho, Andreas
%A Jäschke, Robert
%A Doerfel, Stephan
%A Mitzlaff, Folke
%B Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
%C New York, NY, USA
%D 2012
%I ACM
%P 1--8
%R 10.1145/2365934.2365936
%T Extending FolkRank with Content Data
%U http://doi.acm.org/10.1145/2365934.2365936
%X Real-world tagging datasets have a large proportion of new/ untagged documents. Few approaches for recommending tags to a user for a document address this new item problem, concentrating instead on artificially created post-core datasets where it is guaranteed that the user as well as the document of each test post is known to the system and already has some tags assigned to it. In order to recommend tags for new documents, approaches are required which model documents not only based on the tags assigned to them in the past (if any), but also the content. In this paper we present a novel adaptation to the widely recognised FolkRank tag recommendation algorithm by including content data. We adapt the FolkRank graph to use word nodes instead of document nodes, enabling it to recommend tags for new documents based on their textual content. Our adaptations make FolkRank applicable to post-core 1 ie. the full real-world tagging datasets and address the new item problem in tag recommendation. For comparison, we also apply and evaluate the same methodology of including content on a simpler tag recommendation algorithm. This results in a less expensive recommender which suggests a combination of user related and document content related tags. Including content data into FolkRank shows an improvement over plain FolkRank on full tagging datasets. However, we also observe that our simpler content-aware tag recommender outperforms FolkRank with content data. Our results suggest that an optimisation of the weighting method of FolkRank is required to achieve better results.
%@ 978-1-4503-1638-5 - 1.Kibanov, M.: Untersuchung von Versionsverwaltungssystemen mit Zielsetzung der Optimierung der kollaborativen Entwicklung, (2012).Many new version control systems were developed in the last years. These compete with established systems as they implement some new concepts. These concepts influence the collaborative software development and even redefine it. Before a new system is introduced, it must be selected by product and process requirements. This thesis describes the evaluation of version control systems and the integration of the selected system by the example of one project of Capgemini Germany. Different properties of version control systems were examined and software development processes were analysed. The 3-staged process was applied for the selection of the control system version. This thesis also treats the problems of the integration of the selected system Git into the existing software development processes and project environment.
@mastersthesis{kibanov2012untersuchung,
abstract = {Many new version control systems were developed in the last years. These compete with established systems as they implement some new concepts. These concepts influence the collaborative software development and even redefine it. Before a new system is introduced, it must be selected by product and process requirements. This thesis describes the evaluation of version control systems and the integration of the selected system by the example of one project of Capgemini Germany. Different properties of version control systems were examined and software development processes were analysed. The 3-staged process was applied for the selection of the control system version. This thesis also treats the problems of the integration of the selected system Git into the existing software development processes and project environment.},
author = {Kibanov, Mark},
keywords = {Diplomarbeit},
month = {05},
school = {Humboldt-University of Berlin},
title = {Untersuchung von Versionsverwaltungssystemen mit Zielsetzung der Optimierung der kollaborativen Entwicklung},
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}%0 Thesis
%1 kibanov2012untersuchung
%A Kibanov, Mark
%D 2012
%T Untersuchung von Versionsverwaltungssystemen mit Zielsetzung der Optimierung der kollaborativen Entwicklung
%X Many new version control systems were developed in the last years. These compete with established systems as they implement some new concepts. These concepts influence the collaborative software development and even redefine it. Before a new system is introduced, it must be selected by product and process requirements. This thesis describes the evaluation of version control systems and the integration of the selected system by the example of one project of Capgemini Germany. Different properties of version control systems were examined and software development processes were analysed. The 3-staged process was applied for the selection of the control system version. This thesis also treats the problems of the integration of the selected system Git into the existing software development processes and project environment. - 1.Doerfel, S., Jäschke, R., Stumme, G.: Publication Analysis of the Formal Concept Analysis Community. In: Domenach, F., Ignatov, D., and Poelmans, J. (eds.) Formal Concept Analysis. pp. 77–95. Springer, Berlin/Heidelberg (2012). https://doi.org/10.1007/978-3-642-29892-9_12.We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.
@inproceedings{doerfel2012publication,
abstract = {We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.},
address = {Berlin/Heidelberg},
author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd},
booktitle = {Formal Concept Analysis},
editor = {Domenach, F. and Ignatov, D.I. and Poelmans, J.},
keywords = {icfca},
month = {05},
pages = {77--95},
publisher = {Springer},
series = {Lecture Notes in Artificial Intelligence},
title = {Publication Analysis of the Formal Concept Analysis Community},
volume = 7278,
year = 2012
}%0 Conference Paper
%1 doerfel2012publication
%A Doerfel, Stephan
%A Jäschke, Robert
%A Stumme, Gerd
%B Formal Concept Analysis
%C Berlin/Heidelberg
%D 2012
%E Domenach, F.
%E Ignatov, D.I.
%E Poelmans, J.
%I Springer
%P 77--95
%R 10.1007/978-3-642-29892-9_12
%T Publication Analysis of the Formal Concept Analysis Community
%U https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf
%V 7278
%X We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.
%@ 978-3-642-29891-2 - 1.Balby Marinho, L., Hotho, A., Jäschke, R., Nanopoulos, A., Rendle, S., Schmidt-Thieme, L., Stumme, G., Symeonidis, P.: Recommender Systems for Social Tagging Systems. Springer (2012). https://doi.org/10.1007/978-1-4614-1894-8.Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.
@book{balbymarinho2012recommender,
abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.},
author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.},
keywords = {bookmarking},
month = {02},
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series = {SpringerBriefs in Electrical and Computer Engineering},
title = {Recommender Systems for Social Tagging Systems},
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}%0 Book
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%U http://link.springer.com/book/10.1007/978-1-4614-1894-8
%X Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.
%@ 978-1-4614-1893-1 - 1.Scholz, C., Atzmueller, M., Stumme, G.: {Analyzing the Predictability of Human Contacts: On Influence Factors and Stronger Ties (Extended Abstract)}. In: Proc. LWA 2012 (KDML Special Track). University of Dortmund, Dortmund, Germany (2012).
@inproceedings{SAS:12b,
address = {Dortmund, Germany.},
author = {Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
booktitle = {Proc. LWA 2012 (KDML Special Track)},
keywords = {itegpub},
publisher = {University of Dortmund},
title = {{Analyzing the Predictability of Human Contacts: On Influence Factors and Stronger Ties (Extended Abstract)}},
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}%0 Conference Paper
%1 SAS:12b
%A Scholz, Christoph
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%C Dortmund, Germany.
%D 2012
%I University of Dortmund
%T {Analyzing the Predictability of Human Contacts: On Influence Factors and Stronger Ties (Extended Abstract)}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/2012-lwa-kdml-link-predictability-f2f-extended-abstract.pdf - 1.Lemmerich, F., Becker, M., Atzmueller, M.: {Generic Pattern Trees for Exhaustive Exceptional Model Mining}. In: Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Springer Verlag, Heidelberg, Germany (2012).
@inproceedings{LBA:12,
address = {Heidelberg, Germany},
author = {Lemmerich, Florian and Becker, Martin and Atzmueller, Martin},
booktitle = {Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
keywords = {itegpub},
publisher = {Springer Verlag},
title = {{Generic Pattern Trees for Exhaustive Exceptional Model Mining}},
year = 2012
}%0 Conference Paper
%1 LBA:12
%A Lemmerich, Florian
%A Becker, Martin
%A Atzmueller, Martin
%B Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
%C Heidelberg, Germany
%D 2012
%I Springer Verlag
%T {Generic Pattern Trees for Exhaustive Exceptional Model Mining}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/lemmerich-gp-growth-ecml-pkdd-2012.pdf - 1.Atzmueller, M.: Mining Social Media. Informatik Spektrum. 35, 132–135 (2012).
@article{Atzmueller:12,
author = {Atzmueller, Martin},
journal = {Informatik Spektrum},
keywords = {socialnetworks},
number = 2,
pages = {132-135},
title = {Mining Social Media},
volume = 35,
year = 2012
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%V 35 - 1.Jäschke, R., Hotho, A., Mitzlaff, F., Stumme, G.: Challenges in Tag Recommendations for Collaborative Tagging Systems. In: Pazos Arias, J.J., Fernández Vilas, A., and Díaz Redondo, R.P. (eds.) Recommender Systems for the Social Web. pp. 65–87. Springer, Berlin/Heidelberg (2012). https://doi.org/10.1007/978-3-642-25694-3_3.Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.
@incollection{jaeschke2012challenges,
abstract = {Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.},
address = {Berlin/Heidelberg},
author = {Jäschke, Robert and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd},
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editor = {Pazos Arias, José J. and Fernández Vilas, Ana and Díaz Redondo, Rebeca P.},
keywords = {bookmarking},
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publisher = {Springer},
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%X Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.
%@ 978-3-642-25694-3 - 1.Atzmueller, M., Doerfel, S., Hotho, A., Mitzlaff, F., Stumme, G.: Face-to-Face Contacts at a Conference: Dynamics of Communities and Roles. In: Atzmueller, M., Chin, A., Helic, D., and Hotho, A. (eds.) Modeling and Mining Ubiquitous Social Media - International Workshops MSM 2011, Boston, MA, USA, October 9, 2011, and MUSE 2011, Athens, Greece, September 5, 2011, Revised Selected Papers. pp. 21–39. Springer Berlin Heidelberg, Heidelberg, Germany (2012). https://doi.org/10.1007/978-3-642-33684-3_2.This paper focuses on the community analysis of conference participants using their face-to-face contacts, visited talks, and tracks in a social and ubiquitous conferencing scenario. We consider human face-to-face contacts and perform a dynamic analysis of the number of contacts and their lengths. On these dimensions, we specifically investigate user-interaction and community structure according to different special interest groups during a conference. Additionally, using the community information, we examine different roles and their characteristic elements. The analysis is grounded using real-world conference data capturing community information about participants and their face-to-face contacts. The analysis results indicate, that the face-to-face contacts show inherent community structure grounded using the special interest groups. Furthermore, we provide individual and community-level properties, traces of different behavioral patterns, and characteristic (role) profiles.
@incollection{atzmueller2012facetoface,
abstract = {This paper focuses on the community analysis of conference participants using their face-to-face contacts, visited talks, and tracks in a social and ubiquitous conferencing scenario. We consider human face-to-face contacts and perform a dynamic analysis of the number of contacts and their lengths. On these dimensions, we specifically investigate user-interaction and community structure according to different special interest groups during a conference. Additionally, using the community information, we examine different roles and their characteristic elements. The analysis is grounded using real-world conference data capturing community information about participants and their face-to-face contacts. The analysis results indicate, that the face-to-face contacts show inherent community structure grounded using the special interest groups. Furthermore, we provide individual and community-level properties, traces of different behavioral patterns, and characteristic (role) profiles.},
address = {Heidelberg, Germany},
author = {Atzmueller, Martin and Doerfel, Stephan and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd},
booktitle = {Modeling and Mining Ubiquitous Social Media - International Workshops MSM 2011, Boston, MA, USA, October 9, 2011, and MUSE 2011, Athens, Greece, September 5, 2011, Revised Selected Papers},
editor = {Atzmueller, Martin and Chin, Alvin and Helic, Denis and Hotho, Andreas},
keywords = {contacts},
pages = {21-39},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
title = {Face-to-Face Contacts at a Conference: Dynamics of Communities and Roles},
volume = 7472,
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%X This paper focuses on the community analysis of conference participants using their face-to-face contacts, visited talks, and tracks in a social and ubiquitous conferencing scenario. We consider human face-to-face contacts and perform a dynamic analysis of the number of contacts and their lengths. On these dimensions, we specifically investigate user-interaction and community structure according to different special interest groups during a conference. Additionally, using the community information, we examine different roles and their characteristic elements. The analysis is grounded using real-world conference data capturing community information about participants and their face-to-face contacts. The analysis results indicate, that the face-to-face contacts show inherent community structure grounded using the special interest groups. Furthermore, we provide individual and community-level properties, traces of different behavioral patterns, and characteristic (role) profiles.
%@ 978-3-642-33683-6 - 1.Krause, B., Lerch, H., Hotho, A., Roßnagel, A., Stumme, G.: Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy. Informatik Spektrum. 35, 12–23 (2012).
@article{journals/insk/KrauseLHRS12,
author = {Krause, Beate and Lerch, Hana and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd},
journal = {Informatik Spektrum},
keywords = {bibsonomy},
number = 1,
pages = {12-23},
title = {Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy.},
volume = 35,
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%V 35 - 1.Atzmueller, M., Chin, A., Helic, D., Hotho, A. eds.: Modeling and Mining Ubiquitous Social Media. Springer Verlag, Heidelberg, Germany (2012).
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%V 7472 - 1.Scholz, C., Atzmueller, M., Stumme, G.: {On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties}. In: Proc. Fourth ASE/IEEE International Conference on Social Computing (SocialCom). IEEE Computer Society, Boston, MA, USA (2012).
@inproceedings{SAS:12,
address = {Boston, MA, USA},
author = {Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
booktitle = {Proc. Fourth ASE/IEEE International Conference on Social Computing (SocialCom)},
keywords = {socialnetworks},
publisher = {IEEE Computer Society},
title = {{On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties}},
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%1 SAS:12
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%A Atzmueller, Martin
%A Stumme, Gerd
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%D 2012
%I IEEE Computer Society
%T {On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/scholz-on-f2f-predictability-socialcom-2012.pdf - 1.Behrenbruch, K., Atzmueller, M., Evers, C., Schmidt, L., Stumme, G., Geihs, K.: {A Personality Based Design Approach Using Subgroup Discovery}. In: Human-Centred Software Engineering. pp. 259–266. Springer, Heidelberg, Germany (2012).To facilitate user-centered software engineering, developers need an easy to grasp understanding of the user. The use of personas helps to keep specific user needs in mind during the design process. Technology acceptance is of particular interest for the design of innovative applications previously unknown to potential users. Therefore, our research focuses on defining a typology of relevant user characteristics with respect to technology acceptance and transferring those findings to the description of personas. The presented work focuses on the statistical relationship between technology acceptance and personality. We apply sub-group discovery as a statistical tool. Based on the statistically derived subgroups and patterns we define the mentioned personas to help developers to understand different forms of technology acceptance. By integrating the specifically defined personas into existing methods in the field of software engineering the feasibility of the presented approach is demonstrated.
@incollection{BAESSG:12,
abstract = {To facilitate user-centered software engineering, developers need an easy to grasp understanding of the user. The use of personas helps to keep specific user needs in mind during the design process. Technology acceptance is of particular interest for the design of innovative applications previously unknown to potential users. Therefore, our research focuses on defining a typology of relevant user characteristics with respect to technology acceptance and transferring those findings to the description of personas. The presented work focuses on the statistical relationship between technology acceptance and personality. We apply sub-group discovery as a statistical tool. Based on the statistically derived subgroups and patterns we define the mentioned personas to help developers to understand different forms of technology acceptance. By integrating the specifically defined personas into existing methods in the field of software engineering the feasibility of the presented approach is demonstrated.},
address = {Heidelberg, Germany},
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%C Heidelberg, Germany
%D 2012
%I Springer
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%X To facilitate user-centered software engineering, developers need an easy to grasp understanding of the user. The use of personas helps to keep specific user needs in mind during the design process. Technology acceptance is of particular interest for the design of innovative applications previously unknown to potential users. Therefore, our research focuses on defining a typology of relevant user characteristics with respect to technology acceptance and transferring those findings to the description of personas. The presented work focuses on the statistical relationship between technology acceptance and personality. We apply sub-group discovery as a statistical tool. Based on the statistically derived subgroups and patterns we define the mentioned personas to help developers to understand different forms of technology acceptance. By integrating the specifically defined personas into existing methods in the field of software engineering the feasibility of the presented approach is demonstrated. - 1.Lemmerich, F., Atzmueller, M.: {Describing Locations using Tags and Images: Explorative Pattern Mining in Social Media}. In: {Modeling and Mining Ubiquitous Social Media}. Springer Verlag, Heidelberg, Germany (2012).
@incollection{LA:12,
address = {Heidelberg, Germany},
author = {Lemmerich, Florian and Atzmueller, Martin},
booktitle = {{Modeling and Mining Ubiquitous Social Media}},
keywords = {itegpub},
publisher = {Springer Verlag},
series = {LNAI},
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volume = 7472,
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%V 7472 - 1.Mitzlaff, F., Stumme, G.: Namelings - Discover Given Name Relatedness Based on Data from the Social Web. In: Aberer, K., Flache, A., Jager, W., Liu, L., Tang, J., and Guéret, C. (eds.) SocInfo. pp. 531–534. Springer (2012).
@inproceedings{mitzlaff2012namelings,
author = {Mitzlaff, Folke and Stumme, Gerd},
booktitle = {SocInfo},
editor = {Aberer, Karl and Flache, Andreas and Jager, Wander and Liu, Ling and Tang, Jie and Guéret, Christophe},
keywords = {nameling},
pages = {531-534},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Namelings - Discover Given Name Relatedness Based on Data from the Social Web.},
volume = 7710,
year = 2012
}%0 Conference Paper
%1 mitzlaff2012namelings
%A Mitzlaff, Folke
%A Stumme, Gerd
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%D 2012
%E Aberer, Karl
%E Flache, Andreas
%E Jager, Wander
%E Liu, Ling
%E Tang, Jie
%E Guéret, Christophe
%I Springer
%P 531-534
%T Namelings - Discover Given Name Relatedness Based on Data from the Social Web.
%U https://www.kde.cs.uni-kassel.de/pub/pdf/mitzlaff2012namelings.pdf
%V 7710
%@ 978-3-642-35385-7 - 1.Mitzlaff, F., Stumme, G.: Relatedness of Given Names. Human Journal. 1, 205–217 (2012).As a result of the author's need for help in finding a given namefor the unborn baby, nameling, a search engine for given names, based on data from the ``Social Web'' was born. Within less than six months, more than 35,000 users accessed nameling with more than 300,000 search requests, underpinning the relevance of the underlying research questions. The present work proposes a new approach for discovering relations among given names, based on co-occurrences within Wikipedia. In particular, the task of finding relevant names for a given search query is considered as a ranking task and the performance of different measures of relatedness among given names are evaluated with respect to nameling's actual usage data. We will show that a modification for the PageRank algorithm overcomes limitations imposed by global network characteristics to preferential PageRank computations. By publishing the considered usage data, the research community is stipulated for developing advanced recommendation systems and analyzing influencing factors for the choice of a given name.
@article{mitzlaff2012relatedness,
abstract = {As a result of the author's need for help in finding a given namefor the unborn baby, nameling, a search engine for given names, based on data from the ``Social Web'' was born. Within less than six months, more than 35,000 users accessed nameling with more than 300,000 search requests, underpinning the relevance of the underlying research questions. The present work proposes a new approach for discovering relations among given names, based on co-occurrences within Wikipedia. In particular, the task of finding relevant names for a given search query is considered as a ranking task and the performance of different measures of relatedness among given names are evaluated with respect to nameling's actual usage data. We will show that a modification for the PageRank algorithm overcomes limitations imposed by global network characteristics to preferential PageRank computations. By publishing the considered usage data, the research community is stipulated for developing advanced recommendation systems and analyzing influencing factors for the choice of a given name.},
author = {Mitzlaff, Folke and Stumme, Gerd},
journal = {Human Journal},
keywords = {nameling},
number = 4,
pages = {205-217},
publisher = {Academy of Science and Engineering},
title = {Relatedness of Given Names},
volume = 1,
year = 2012
}%0 Journal Article
%1 mitzlaff2012relatedness
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%V 1
%X As a result of the author's need for help in finding a given namefor the unborn baby, nameling, a search engine for given names, based on data from the ``Social Web'' was born. Within less than six months, more than 35,000 users accessed nameling with more than 300,000 search requests, underpinning the relevance of the underlying research questions. The present work proposes a new approach for discovering relations among given names, based on co-occurrences within Wikipedia. In particular, the task of finding relevant names for a given search query is considered as a ranking task and the performance of different measures of relatedness among given names are evaluated with respect to nameling's actual usage data. We will show that a modification for the PageRank algorithm overcomes limitations imposed by global network characteristics to preferential PageRank computations. By publishing the considered usage data, the research community is stipulated for developing advanced recommendation systems and analyzing influencing factors for the choice of a given name. - 1.Atzmueller, M., Hotho, A. eds.: {Proceedings of the Third International Workshop on Mining Ubiquitous and Social Environments (MUSE 2012)}. Workshop Notes, Bristol, UK (2012).
@book{AH:12,
address = {Bristol, UK},
editor = {Atzmueller, Martin and Hotho, Andreas},
keywords = {muse},
publisher = {Workshop Notes},
title = {{Proceedings of the Third International Workshop on Mining Ubiquitous and Social Environments (MUSE 2012)}},
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%U https://www.kde.cs.uni-kassel.de/ws/muse2012/proceedings.pdf - 1.Landia, N., Anand, S.S., Hotho, A., J{ä}schke, R., Doerfel, S., Mitzlaff, F.: Extending FolkRank with content data. In: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web. pp. 1–8. ACM, Dublin, Ireland (2012). https://doi.org/10.1145/2365934.2365936.Real-world tagging datasets have a large proportion of new/ untagged documents. Few approaches for recommending tags to a user for a document address this new item problem, concentrating instead on artificially created post-core datasets where it is guaranteed that the user as well as the document of each test post is known to the system and already has some tags assigned to it. In order to recommend tags for new documents, approaches are required which model documents not only based on the tags assigned to them in the past (if any), but also the content. In this paper we present a novel adaptation to the widely recognised FolkRank tag recommendation algorithm by including content data. We adapt the FolkRank graph to use word nodes instead of document nodes, enabling it to recommend tags for new documents based on their textual content. Our adaptations make FolkRank applicable to post-core 1 ie. the full real-world tagging datasets and address the new item problem in tag recommendation. For comparison, we also apply and evaluate the same methodology of including content on a simpler tag recommendation algorithm. This results in a less expensive recommender which suggests a combination of user related and document content related tags.
Including content data into FolkRank shows an improvement over plain FolkRank on full tagging datasets. However, we also observe that our simpler content-aware tag recommender outperforms FolkRank with content data. Our results suggest that an optimisation of the weighting method of FolkRank is required to achieve better results.
@inproceedings{Landia:2012:EFC:2365934.2365936,
abstract = {Real-world tagging datasets have a large proportion of new/ untagged documents. Few approaches for recommending tags to a user for a document address this new item problem, concentrating instead on artificially created post-core datasets where it is guaranteed that the user as well as the document of each test post is known to the system and already has some tags assigned to it. In order to recommend tags for new documents, approaches are required which model documents not only based on the tags assigned to them in the past (if any), but also the content. In this paper we present a novel adaptation to the widely recognised FolkRank tag recommendation algorithm by including content data. We adapt the FolkRank graph to use word nodes instead of document nodes, enabling it to recommend tags for new documents based on their textual content. Our adaptations make FolkRank applicable to post-core 1 ie. the full real-world tagging datasets and address the new item problem in tag recommendation. For comparison, we also apply and evaluate the same methodology of including content on a simpler tag recommendation algorithm. This results in a less expensive recommender which suggests a combination of user related and document content related tags.Including content data into FolkRank shows an improvement over plain FolkRank on full tagging datasets. However, we also observe that our simpler content-aware tag recommender outperforms FolkRank with content data. Our results suggest that an optimisation of the weighting method of FolkRank is required to achieve better results.},
address = {New York, NY, USA},
author = {Landia, Nikolas and Anand, Sarabjot Singh and Hotho, Andreas and J{ä}schke, Robert and Doerfel, Stephan and Mitzlaff, Folke},
booktitle = {Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web},
keywords = {bookmarking},
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publisher = {ACM},
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title = {Extending FolkRank with content data},
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}%0 Conference Paper
%1 Landia:2012:EFC:2365934.2365936
%A Landia, Nikolas
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%A Doerfel, Stephan
%A Mitzlaff, Folke
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%C New York, NY, USA
%D 2012
%I ACM
%P 1--8
%R 10.1145/2365934.2365936
%T Extending FolkRank with content data
%U http://doi.acm.org/10.1145/2365934.2365936
%X Real-world tagging datasets have a large proportion of new/ untagged documents. Few approaches for recommending tags to a user for a document address this new item problem, concentrating instead on artificially created post-core datasets where it is guaranteed that the user as well as the document of each test post is known to the system and already has some tags assigned to it. In order to recommend tags for new documents, approaches are required which model documents not only based on the tags assigned to them in the past (if any), but also the content. In this paper we present a novel adaptation to the widely recognised FolkRank tag recommendation algorithm by including content data. We adapt the FolkRank graph to use word nodes instead of document nodes, enabling it to recommend tags for new documents based on their textual content. Our adaptations make FolkRank applicable to post-core 1 ie. the full real-world tagging datasets and address the new item problem in tag recommendation. For comparison, we also apply and evaluate the same methodology of including content on a simpler tag recommendation algorithm. This results in a less expensive recommender which suggests a combination of user related and document content related tags.Including content data into FolkRank shows an improvement over plain FolkRank on full tagging datasets. However, we also observe that our simpler content-aware tag recommender outperforms FolkRank with content data. Our results suggest that an optimisation of the weighting method of FolkRank is required to achieve better results.
%@ 978-1-4503-1638-5 - 1.Klügl, P., Toepfer, M., Lemmerich, F., Hotho, A., Puppe, F.: Stacked Conditional Random Fields Exploiting Structural Consistencies. In: Carmona, P.L., Sánchez, J.S., and Fred, A. (eds.) Proceedings of 1st International Conference on Pattern Recognition Applications and Methods ICPRAM. pp. 240–248. SciTePress, Vilamoura, Algarve, Portugal (2012).Conditional Random Fields CRF are popular methods for labeling unstructured or textual data. Like many machine learning approaches these undirected graphical models assume the instances to be independently distributed. However, in real world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. The approach incorporates three successive steps of inference: First, an initial CRF processes single instances as usual. Next, we apply rule learning collectively on all labeled outputs of one context to acquire descriptions of its specific properties. Finally, we utilize these descriptions as dynamic and high quality features in an additional stacked CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.
@inproceedings{kluegl2012stacked,
abstract = {Conditional Random Fields CRF are popular methods for labeling unstructured or textual data. Like many machine learning approaches these undirected graphical models assume the instances to be independently distributed. However, in real world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. The approach incorporates three successive steps of inference: First, an initial CRF processes single instances as usual. Next, we apply rule learning collectively on all labeled outputs of one context to acquire descriptions of its specific properties. Finally, we utilize these descriptions as dynamic and high quality features in an additional stacked CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.},
address = {Vilamoura, Algarve, Portugal},
author = {Klügl, Peter and Toepfer, Martin and Lemmerich, Florian and Hotho, Andreas and Puppe, Frank},
booktitle = {Proceedings of 1st International Conference on Pattern Recognition Applications and Methods ICPRAM},
editor = {Carmona, Pedro Latorre and Sánchez, J. Salvador and Fred, Ana},
keywords = {fields},
pages = {240-248},
publisher = {SciTePress},
title = {Stacked Conditional Random Fields Exploiting Structural Consistencies},
year = 2012
}%0 Conference Paper
%1 kluegl2012stacked
%A Klügl, Peter
%A Toepfer, Martin
%A Lemmerich, Florian
%A Hotho, Andreas
%A Puppe, Frank
%B Proceedings of 1st International Conference on Pattern Recognition Applications and Methods ICPRAM
%C Vilamoura, Algarve, Portugal
%D 2012
%E Carmona, Pedro Latorre
%E Sánchez, J. Salvador
%E Fred, Ana
%I SciTePress
%P 240-248
%T Stacked Conditional Random Fields Exploiting Structural Consistencies
%U http://ki.informatik.uni-wuerzburg.de/papers/pkluegl/2012-ICPRAM-StackedCRF.pdf
%X Conditional Random Fields CRF are popular methods for labeling unstructured or textual data. Like many machine learning approaches these undirected graphical models assume the instances to be independently distributed. However, in real world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional structural consistencies. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. The approach incorporates three successive steps of inference: First, an initial CRF processes single instances as usual. Next, we apply rule learning collectively on all labeled outputs of one context to acquire descriptions of its specific properties. Finally, we utilize these descriptions as dynamic and high quality features in an additional stacked CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error. - 1.Mitzlaff, F., Stumme, G.: Ranking Given Names. In: Marathe, M. and Contractor, N. (eds.) Proceedings of the 1st ASE International Conference on Social Informatics. pp. 185–191. IEEE computer society (2012).
@inproceedings{mitzlaff2012ranking,
author = {Mitzlaff, Folke and Stumme, Gerd},
booktitle = {Proceedings of the 1st ASE International Conference on Social Informatics},
editor = {Marathe, Madhav and Contractor, Noshir},
keywords = {nameling},
pages = {185-191},
publisher = {IEEE computer society},
title = {Ranking Given Names},
year = 2012
}%0 Conference Paper
%1 mitzlaff2012ranking
%A Mitzlaff, Folke
%A Stumme, Gerd
%B Proceedings of the 1st ASE International Conference on Social Informatics
%D 2012
%E Marathe, Madhav
%E Contractor, Noshir
%I IEEE computer society
%P 185-191
%T Ranking Given Names - 1.Atzmueller, M.: {Onto Collective Intelligence in Social Media: Exemplary Applications and Perspectives}. In: Proc. 3rd International Workshop on Modeling Social Media (MSM 2012), Hypertext 2012. ACM Press, New York, NY, USA (2012).
@inproceedings{Atzmueller:12b,
address = {New York, NY, USA},
author = {Atzmueller, Martin},
booktitle = {Proc. 3rd International Workshop on Modeling Social Media (MSM 2012), Hypertext 2012},
keywords = {itegpub},
publisher = {ACM Press},
title = {{Onto Collective Intelligence in Social Media: Exemplary Applications and Perspectives}},
year = 2012
}%0 Conference Paper
%1 Atzmueller:12b
%A Atzmueller, Martin
%B Proc. 3rd International Workshop on Modeling Social Media (MSM 2012), Hypertext 2012
%C New York, NY, USA
%D 2012
%I ACM Press
%T {Onto Collective Intelligence in Social Media: Exemplary Applications and Perspectives} - 1.Atzmueller, M., Lemmerich, F.: {VIKAMINE - Open-Source Subgroup Discovery, Pattern Mining, and Analytics}. In: Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Springer Verlag, Heidelberg, Germany (2012).
@inproceedings{AL:12a,
address = {Heidelberg, Germany},
author = {Atzmueller, Martin and Lemmerich, Florian},
booktitle = {Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
keywords = {itegpub},
publisher = {Springer Verlag},
title = {{VIKAMINE - Open-Source Subgroup Discovery, Pattern Mining, and Analytics}},
year = 2012
}%0 Conference Paper
%1 AL:12a
%A Atzmueller, Martin
%A Lemmerich, Florian
%B Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
%C Heidelberg, Germany
%D 2012
%I Springer Verlag
%T {VIKAMINE - Open-Source Subgroup Discovery, Pattern Mining, and Analytics}
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-vikamine2-ecml-pkdd-2012.pdf - 1.Atzmueller, M.: {Mining Social Media: Key Players, Sentiments, and Communities}. WIREs: Data Mining and Knowledge Discovery. 1069, (2012).
@article{Atzmueller:12c,
author = {Atzmueller, Martin},
journal = {WIREs: Data Mining and Knowledge Discovery},
keywords = {mining},
title = {{Mining Social Media: Key Players, Sentiments, and Communities}},
volume = 1069,
year = 2012
}%0 Journal Article
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%J WIREs: Data Mining and Knowledge Discovery
%T {Mining Social Media: Key Players, Sentiments, and Communities}
%V 1069 - 1.Seipel, D., Neubeck, P., Köhler, S., Atzmueller, M.: {Mining Complex Event Patterns in Computer Networks}. In: Proc. ECML/PKDD Workshop on New Frontiers in Mining Complex Patterns. , Bristol, UK (2012).
@inproceedings{SNKA:12,
address = {Bristol, UK},
author = {Seipel, Dietmar and Neubeck, Philipp and Köhler, Stefan and Atzmueller, Martin},
booktitle = {Proc. ECML/PKDD Workshop on New Frontiers in Mining Complex Patterns},
keywords = {event},
title = {{Mining Complex Event Patterns in Computer Networks}},
year = 2012
}%0 Conference Paper
%1 SNKA:12
%A Seipel, Dietmar
%A Neubeck, Philipp
%A Köhler, Stefan
%A Atzmueller, Martin
%B Proc. ECML/PKDD Workshop on New Frontiers in Mining Complex Patterns
%C Bristol, UK
%D 2012
%T {Mining Complex Event Patterns in Computer Networks} - 1.Chin, A., Atzmueller, M., Helic, D. eds.: {Proceedings MSM 2012: Workshop on Modeling Social Media -- Collective Intelligence in Social Media}. ACM Press, New York, NY, USA (2012).
@proceedings{CAH:12,
address = {New York, NY, USA},
editor = {Chin, Alvin and Atzmueller, Martin and Helic, Denis},
keywords = {itegpub},
publisher = {ACM Press},
title = {{Proceedings MSM 2012: Workshop on Modeling Social Media -- Collective Intelligence in Social Media}},
year = 2012
}%0 Conference Proceedings
%1 CAH:12
%C New York, NY, USA
%D 2012
%E Chin, Alvin
%E Atzmueller, Martin
%E Helic, Denis
%I ACM Press
%T {Proceedings MSM 2012: Workshop on Modeling Social Media -- Collective Intelligence in Social Media} - 1.Mobasher, B., Jannach, D., Geyer, W., Hotho, A.: RSWeb ’12: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web. ACM, Dublin, Ireland (2012).The new opportunities for applying recommendation techniques within Social Web platforms and applications as well as the various new sources of information which have become available in the Web 2.0 and can be incorporated in future recommender applications are a strong driving factor in current recommender system research for various reasons:
(1) Social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation.
(2) New application areas for recommender systems emerge with the popularity of the Social Web. Recommenders cannot only be used to sort and filter Web 2.0 and social network information, they can also support users in the information sharing process, e.g., by recommending suitable tags during folksonomy development.
(3) Recommender technology can assist Social Web systems through increasing adoption and participation and sustaining membership. Through targeted and timely intervention which stimulates traffic and interaction, recommender technology can play its role in sustaining the success of the Social Web.
(4) The Social Web also presents new challenges for recommender systems, such as the complicated nature of human-to-human interaction which comes into play when recommending people and can require more interactive and richer recommender systems user interfaces.
The technical papers appearing in these proceedings aim to explore and understand challenges and new opportunities for recommender systems in the Social Web and were selected in a formal review process by an international program committee.
Overall, we received 13 paper submissions from 12 different countries, out of which 7 long papers and 1 short paper were selected for presentation and inclusion in the proceedings. The submitted papers addressed a variety of topics related to Social Web recommender systems from the use of microblogging data for personalization over new tag recommendation approaches to social media-based personalization of news.
@proceedings{Mobasher:2012:2365934,
abstract = {The new opportunities for applying recommendation techniques within Social Web platforms and applications as well as the various new sources of information which have become available in the Web 2.0 and can be incorporated in future recommender applications are a strong driving factor in current recommender system research for various reasons:(1) Social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation.
(2) New application areas for recommender systems emerge with the popularity of the Social Web. Recommenders cannot only be used to sort and filter Web 2.0 and social network information, they can also support users in the information sharing process, e.g., by recommending suitable tags during folksonomy development.
(3) Recommender technology can assist Social Web systems through increasing adoption and participation and sustaining membership. Through targeted and timely intervention which stimulates traffic and interaction, recommender technology can play its role in sustaining the success of the Social Web.
(4) The Social Web also presents new challenges for recommender systems, such as the complicated nature of human-to-human interaction which comes into play when recommending people and can require more interactive and richer recommender systems user interfaces.
The technical papers appearing in these proceedings aim to explore and understand challenges and new opportunities for recommender systems in the Social Web and were selected in a formal review process by an international program committee.
Overall, we received 13 paper submissions from 12 different countries, out of which 7 long papers and 1 short paper were selected for presentation and inclusion in the proceedings. The submitted papers addressed a variety of topics related to Social Web recommender systems from the use of microblogging data for personalization over new tag recommendation approaches to social media-based personalization of news.},
address = {New York, NY, USA},
author = {Mobasher, Bamshad and Jannach, Dietmar and Geyer, Werner and Hotho, Andreas},
keywords = {rsweb},
note = 609126,
publisher = {ACM},
title = {RSWeb '12: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web},
year = 2012
}%0 Conference Proceedings
%1 Mobasher:2012:2365934
%A Mobasher, Bamshad
%A Jannach, Dietmar
%A Geyer, Werner
%A Hotho, Andreas
%C New York, NY, USA
%D 2012
%I ACM
%T RSWeb '12: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
%X The new opportunities for applying recommendation techniques within Social Web platforms and applications as well as the various new sources of information which have become available in the Web 2.0 and can be incorporated in future recommender applications are a strong driving factor in current recommender system research for various reasons:(1) Social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation.
(2) New application areas for recommender systems emerge with the popularity of the Social Web. Recommenders cannot only be used to sort and filter Web 2.0 and social network information, they can also support users in the information sharing process, e.g., by recommending suitable tags during folksonomy development.
(3) Recommender technology can assist Social Web systems through increasing adoption and participation and sustaining membership. Through targeted and timely intervention which stimulates traffic and interaction, recommender technology can play its role in sustaining the success of the Social Web.
(4) The Social Web also presents new challenges for recommender systems, such as the complicated nature of human-to-human interaction which comes into play when recommending people and can require more interactive and richer recommender systems user interfaces.
The technical papers appearing in these proceedings aim to explore and understand challenges and new opportunities for recommender systems in the Social Web and were selected in a formal review process by an international program committee.
Overall, we received 13 paper submissions from 12 different countries, out of which 7 long papers and 1 short paper were selected for presentation and inclusion in the proceedings. The submitted papers addressed a variety of topics related to Social Web recommender systems from the use of microblogging data for personalization over new tag recommendation approaches to social media-based personalization of news.
%@ 978-1-4503-1638-5 - 1.Mobasher, B., Jannach, D., Geyer, W., Hotho, A.: 4th ACM RecSys workshop on recommender systems and the social web. In: Cunningham, P., Hurley, N.J., Guy, I., and Anand, S.S. (eds.) RecSys. pp. 345–346. ACM (2012).
@inproceedings{conf/recsys/MobasherJGH12,
author = {Mobasher, Bamshad and Jannach, Dietmar and Geyer, Werner and Hotho, Andreas},
booktitle = {RecSys},
crossref = {conf/recsys/2012},
editor = {Cunningham, Padraig and Hurley, Neil J. and Guy, Ido and Anand, Sarabjot Singh},
keywords = {recommender},
pages = {345-346},
publisher = {ACM},
title = {4th ACM RecSys workshop on recommender systems and the social web.},
year = 2012
}%0 Conference Paper
%1 conf/recsys/MobasherJGH12
%A Mobasher, Bamshad
%A Jannach, Dietmar
%A Geyer, Werner
%A Hotho, Andreas
%B RecSys
%D 2012
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%E Hurley, Neil J.
%E Guy, Ido
%E Anand, Sarabjot Singh
%I ACM
%P 345-346
%T 4th ACM RecSys workshop on recommender systems and the social web.
%U http://dblp.uni-trier.de/db/conf/recsys/recsys2012.html#MobasherJGH12
%@ 978-1-4503-1270-7 - 1.Said, A., Tikk, D., Hotho, A.: The challenge of recommender systems challenges. In: Cunningham, P., Hurley, N.J., Guy, I., and Anand, S.S. (eds.) RecSys. pp. 9–10. ACM (2012).
@inproceedings{conf/recsys/SaidTH12,
author = {Said, Alan and Tikk, Domonkos and Hotho, Andreas},
booktitle = {RecSys},
crossref = {conf/recsys/2012},
editor = {Cunningham, Padraig and Hurley, Neil J. and Guy, Ido and Anand, Sarabjot Singh},
keywords = {recommender},
pages = {9-10},
publisher = {ACM},
title = {The challenge of recommender systems challenges.},
year = 2012
}%0 Conference Paper
%1 conf/recsys/SaidTH12
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%A Tikk, Domonkos
%A Hotho, Andreas
%B RecSys
%D 2012
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%E Hurley, Neil J.
%E Guy, Ido
%E Anand, Sarabjot Singh
%I ACM
%P 9-10
%T The challenge of recommender systems challenges.
%U http://dblp.uni-trier.de/db/conf/recsys/recsys2012.html#SaidTH12
%@ 978-1-4503-1270-7 - 1.Hotho, A.: Publikationen im Web 2.0. Informatik-Spektrum. 1–5 (2012). https://doi.org/10.1007/s00287-012-0653-0.
@article{hotho2012publikationen,
address = {Berlin / Heidelberg},
author = {Hotho, Andreas},
journal = {Informatik-Spektrum},
keywords = {publications},
pages = {1-5},
publisher = {Springer},
title = {Publikationen im Web 2.0},
year = 2012
}%0 Journal Article
%1 hotho2012publikationen
%A Hotho, Andreas
%C Berlin / Heidelberg
%D 2012
%I Springer
%J Informatik-Spektrum
%P 1-5
%R 10.1007/s00287-012-0653-0
%T Publikationen im Web 2.0
%U http://dx.doi.org/10.1007/s00287-012-0653-0 - 1.Klügl, P., Toepfer, M., Lemmerich, F., Hotho, A., Puppe, F.: Collective Information Extraction with Context-Specific Consistencies. In: Flach, P.A., Bie, T.D., and Cristianini, N. (eds.) ECML/PKDD (1). pp. 728–743. Springer (2012).
@inproceedings{conf/pkdd/KluglTLHP12,
author = {Klügl, Peter and Toepfer, Martin and Lemmerich, Florian and Hotho, Andreas and Puppe, Frank},
booktitle = {ECML/PKDD (1)},
crossref = {conf/pkdd/2012-1},
editor = {Flach, Peter A. and Bie, Tijl De and Cristianini, Nello},
keywords = {extraction},
pages = {728-743},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Collective Information Extraction with Context-Specific Consistencies.},
volume = 7523,
year = 2012
}%0 Conference Paper
%1 conf/pkdd/KluglTLHP12
%A Klügl, Peter
%A Toepfer, Martin
%A Lemmerich, Florian
%A Hotho, Andreas
%A Puppe, Frank
%B ECML/PKDD (1)
%D 2012
%E Flach, Peter A.
%E Bie, Tijl De
%E Cristianini, Nello
%I Springer
%P 728-743
%T Collective Information Extraction with Context-Specific Consistencies.
%U http://dblp.uni-trier.de/db/conf/pkdd/pkdd2012-1.html#KluglTLHP12
%V 7523
%@ 978-3-642-33459-7 - 1.Macek, B.E., Scholz, C., Atzmueller, M., Stumme, G.: Anatomy of a Conference. In: Proc. 23rd ACM Conference on Hypertext and Social Media, HT ’12 (2012).
@inproceedings{MASS:12,
author = {Macek, Bjoern Elmar and Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
booktitle = {Proc. 23rd ACM Conference on Hypertext and Social Media, HT '12},
keywords = {itegpub},
title = {Anatomy of a Conference},
year = 2012
}%0 Conference Paper
%1 MASS:12
%A Macek, Bjoern Elmar
%A Scholz, Christoph
%A Atzmueller, Martin
%A Stumme, Gerd
%B Proc. 23rd ACM Conference on Hypertext and Social Media, HT '12
%D 2012
%T Anatomy of a Conference
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/macek-anatomy-of-a-conference-hypertext-2012.pdf
2011
- 1.Doerfel, S.: A Context-Based Description of the Doubly Founded Concept Lattices in the Variety Generated by M_3. In: Valtchev, P. and Jäschke, R. (eds.) Formal Concept Analysis. pp. 93–106. Springer, Berlin / Heidelberg (2011). https://doi.org/10.1007/978-3-642-20514-9_9.In universal algebra and in lattice theory the notion of varieties is very prominent, since varieties describe the classes of all algebras (or of all lattices) modeling a given set of equations. While a comprehensive translation of that notion to a similar notion of varieties of complete lattices – and thus to Formal Concept Analysis – has not yet been accomplished, some characterizations of the doubly founded complete lattices of some special varieties (e.g. the variety of modular or that of distributive lattices) have been discovered. In this paper we use the well-known arrow relations to give a characterization of the formal contexts of doubly founded concept lattices in the variety that is generated by M 3 – the smallest modular, non-distributive lattice variety.
@inproceedings{doerfel2011contextbased,
abstract = {In universal algebra and in lattice theory the notion of varieties is very prominent, since varieties describe the classes of all algebras (or of all lattices) modeling a given set of equations. While a comprehensive translation of that notion to a similar notion of varieties of complete lattices – and thus to Formal Concept Analysis – has not yet been accomplished, some characterizations of the doubly founded complete lattices of some special varieties (e.g. the variety of modular or that of distributive lattices) have been discovered. In this paper we use the well-known arrow relations to give a characterization of the formal contexts of doubly founded concept lattices in the variety that is generated by M 3 – the smallest modular, non-distributive lattice variety.},
address = {Berlin / Heidelberg},
author = {Doerfel, Stephan},
booktitle = {Formal Concept Analysis},
editor = {Valtchev, Petko and Jäschke, Robert},
keywords = {itegpub},
pages = {93-106},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {A Context-Based Description of the Doubly Founded Concept Lattices in the Variety Generated by M_3},
volume = 6628,
year = 2011
}%0 Conference Paper
%1 doerfel2011contextbased
%A Doerfel, Stephan
%B Formal Concept Analysis
%C Berlin / Heidelberg
%D 2011
%E Valtchev, Petko
%E Jäschke, Robert
%I Springer
%P 93-106
%R 10.1007/978-3-642-20514-9_9
%T A Context-Based Description of the Doubly Founded Concept Lattices in the Variety Generated by M_3
%U http://dx.doi.org/10.1007/978-3-642-20514-9_9
%V 6628
%X In universal algebra and in lattice theory the notion of varieties is very prominent, since varieties describe the classes of all algebras (or of all lattices) modeling a given set of equations. While a comprehensive translation of that notion to a similar notion of varieties of complete lattices – and thus to Formal Concept Analysis – has not yet been accomplished, some characterizations of the doubly founded complete lattices of some special varieties (e.g. the variety of modular or that of distributive lattices) have been discovered. In this paper we use the well-known arrow relations to give a characterization of the formal contexts of doubly founded concept lattices in the variety that is generated by M 3 – the smallest modular, non-distributive lattice variety. - 1.Atzmüller, M., Benz, D., Doerfel, S., Hotho, A., Jäschke, R., Macek, B.-E., {Mitzlaff, F., Stumme, G.: Enhancing Social Interactions at Conferences. it - Information Technology, (53)3:101--107, Oldenbourg Wissenschaftsverlag GmbH, May 2011. (2011).
@article{L3S_518093b0d815c42951de5634127244d1b677c06f,
author = {Atzmüller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Björn-Elmar and {Mitzlaff, Folke}, Christoph Scholz and Stumme, Gerd},
journal = {it - Information Technology, (53)3:101--107, Oldenbourg Wissenschaftsverlag GmbH, May 2011},
keywords = 2011,
title = {Enhancing Social Interactions at Conferences},
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}%0 Journal Article
%1 L3S_518093b0d815c42951de5634127244d1b677c06f
%A Atzmüller, Martin
%A Benz, Dominik
%A Doerfel, Stephan
%A Hotho, Andreas
%A Jäschke, Robert
%A Macek, Björn-Elmar
%A {Mitzlaff, Folke}
%A Stumme, Gerd
%D 2011
%J it - Information Technology, (53)3:101--107, Oldenbourg Wissenschaftsverlag GmbH, May 2011
%T Enhancing Social Interactions at Conferences - 1.Navarro Bullock, B., Lerch, H., Ro\ssnagel, A., Hotho, A., Stumme, G.: Privacy-aware spam detection in social bookmarking systems. In: Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies. pp. 15:1–15:8. ACM, Graz, Austria (2011). https://doi.org/10.1145/2024288.2024306.With the increased popularity of Web 2.0 services in the last years data privacy has become a major concern for users. The more personal data users reveal, the more difficult it becomes to control its disclosure in the web. However, for Web 2.0 service providers, the data provided by users is a valuable source for offering effective, personalised data mining services. One major application is the detection of spam in social bookmarking systems: in order to prevent a decrease of content quality, providers need to distinguish spammers and exclude them from the system. They thereby experience a conflict of interests: on the one hand, they need to identify spammers based on the information they collect about users, on the other hand, they need to respect privacy concerns and process as few personal data as possible. It would therefore be of tremendous help for system developers and users to know which personal data are needed for spam detection and which can be ignored. In this paper we address these questions by presenting a data privacy aware feature engineering approach. It consists of the design of features for spam classification which are evaluated according to both, performance and privacy conditions. Experiments using data from the social bookmarking system BibSonomy show that both conditions must not exclude each other.
@inproceedings{bullock2011privacyaware,
abstract = {With the increased popularity of Web 2.0 services in the last years data privacy has become a major concern for users. The more personal data users reveal, the more difficult it becomes to control its disclosure in the web. However, for Web 2.0 service providers, the data provided by users is a valuable source for offering effective, personalised data mining services. One major application is the detection of spam in social bookmarking systems: in order to prevent a decrease of content quality, providers need to distinguish spammers and exclude them from the system. They thereby experience a conflict of interests: on the one hand, they need to identify spammers based on the information they collect about users, on the other hand, they need to respect privacy concerns and process as few personal data as possible. It would therefore be of tremendous help for system developers and users to know which personal data are needed for spam detection and which can be ignored. In this paper we address these questions by presenting a data privacy aware feature engineering approach. It consists of the design of features for spam classification which are evaluated according to both, performance and privacy conditions. Experiments using data from the social bookmarking system BibSonomy show that both conditions must not exclude each other.},
address = {New York, NY, USA},
author = {Navarro Bullock, Beate and Lerch, Hana and Ro\ssnagel, Alexander and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies},
keywords = {classification},
pages = {15:1--15:8},
publisher = {ACM},
series = {i-KNOW '11},
title = {Privacy-aware spam detection in social bookmarking systems},
year = 2011
}%0 Conference Paper
%1 bullock2011privacyaware
%A Navarro Bullock, Beate
%A Lerch, Hana
%A Ro\ssnagel, Alexander
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
%C New York, NY, USA
%D 2011
%I ACM
%P 15:1--15:8
%R 10.1145/2024288.2024306
%T Privacy-aware spam detection in social bookmarking systems
%U http://doi.acm.org/10.1145/2024288.2024306
%X With the increased popularity of Web 2.0 services in the last years data privacy has become a major concern for users. The more personal data users reveal, the more difficult it becomes to control its disclosure in the web. However, for Web 2.0 service providers, the data provided by users is a valuable source for offering effective, personalised data mining services. One major application is the detection of spam in social bookmarking systems: in order to prevent a decrease of content quality, providers need to distinguish spammers and exclude them from the system. They thereby experience a conflict of interests: on the one hand, they need to identify spammers based on the information they collect about users, on the other hand, they need to respect privacy concerns and process as few personal data as possible. It would therefore be of tremendous help for system developers and users to know which personal data are needed for spam detection and which can be ignored. In this paper we address these questions by presenting a data privacy aware feature engineering approach. It consists of the design of features for spam classification which are evaluated according to both, performance and privacy conditions. Experiments using data from the social bookmarking system BibSonomy show that both conditions must not exclude each other.
%@ 978-1-4503-0732-1 - 1.Balby Marinho, L., Nanopoulos, A., Schmidt-Thieme, L., Jäschke, R., Hotho, A., Stumme, G., Symeonidis, P.: Social Tagging Recommender Systems. In: Ricci, F., Rokach, L., Shapira, B., and Kantor, P.B. (eds.) Recommender Systems Handbook. pp. 615–644. Springer, New York (2011). https://doi.org/10.1007/978-0-387-85820-3_19.The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while STS bring new opportunities, they revive old problems, such as information overload. Recommender Systems are well known applications for increasing the level of relevant content over the noise that continuously grows as more and more content becomes available online. In STS however, we face new challenges. Users are interested in finding not only content, but also tags and even other users. Moreover, while traditional recommender systems usually operate over 2-way data arrays, STS data is represented as a third-order tensor or a hypergraph with hyperedges denoting (user, resource, tag) triples. In this chapter, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve STS.We describe (a) novel facets of recommenders for STS, such as user, resource, and tag recommenders, (b) new approaches and algorithms for dealing with the ternary nature of STS data, and (c) recommender systems deployed in real world STS. Moreover, a concise comparison between existing works is presented, through which we identify and point out new research directions.
@incollection{marinho2011social,
abstract = {The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while STS bring new opportunities, they revive old problems, such as information overload. Recommender Systems are well known applications for increasing the level of relevant content over the noise that continuously grows as more and more content becomes available online. In STS however, we face new challenges. Users are interested in finding not only content, but also tags and even other users. Moreover, while traditional recommender systems usually operate over 2-way data arrays, STS data is represented as a third-order tensor or a hypergraph with hyperedges denoting (user, resource, tag) triples. In this chapter, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve STS.We describe (a) novel facets of recommenders for STS, such as user, resource, and tag recommenders, (b) new approaches and algorithms for dealing with the ternary nature of STS data, and (c) recommender systems deployed in real world STS. Moreover, a concise comparison between existing works is presented, through which we identify and point out new research directions.},
address = {New York},
author = {Balby Marinho, Leandro and Nanopoulos, Alexandros and Schmidt-Thieme, Lars and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd and Symeonidis, Panagiotis},
booktitle = {Recommender Systems Handbook},
editor = {Ricci, Francesco and Rokach, Lior and Shapira, Bracha and Kantor, Paul B.},
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}%0 Book Section
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%A Jäschke, Robert
%A Hotho, Andreas
%A Stumme, Gerd
%A Symeonidis, Panagiotis
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%E Rokach, Lior
%E Shapira, Bracha
%E Kantor, Paul B.
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%T Social Tagging Recommender Systems
%U http://dx.doi.org/10.1007/978-0-387-85820-3_19
%X The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while STS bring new opportunities, they revive old problems, such as information overload. Recommender Systems are well known applications for increasing the level of relevant content over the noise that continuously grows as more and more content becomes available online. In STS however, we face new challenges. Users are interested in finding not only content, but also tags and even other users. Moreover, while traditional recommender systems usually operate over 2-way data arrays, STS data is represented as a third-order tensor or a hypergraph with hyperedges denoting (user, resource, tag) triples. In this chapter, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve STS.We describe (a) novel facets of recommenders for STS, such as user, resource, and tag recommenders, (b) new approaches and algorithms for dealing with the ternary nature of STS data, and (c) recommender systems deployed in real world STS. Moreover, a concise comparison between existing works is presented, through which we identify and point out new research directions.
%@ 978-0-387-85820-3 - 1.Behrenbruch, K., Atzmueller, M., Kniewel, R., Hoberg, S., Stumme, G., Schmidt, L.: Gestaltung technisch-sozialer Vernetzung in der Arbeitsorganisation: Untersuchung zur Nutzerakzeptanz von RFID-Technologie. In: GfA-Frühjahrskongress. , Chemnitz (2011).
@inproceedings{BAKHSS:11,
address = {Chemnitz},
author = {Behrenbruch, Kay and Atzmueller, Martin and Kniewel, Romy and Hoberg, Sebastian and Stumme, Gerd and Schmidt, Ludger},
booktitle = {GfA-Frühjahrskongress},
keywords = {itegpub},
title = {Gestaltung technisch-sozialer Vernetzung in der Arbeitsorganisation: Untersuchung zur Nutzerakzeptanz von RFID-Technologie},
year = 2011
}%0 Conference Paper
%1 BAKHSS:11
%A Behrenbruch, Kay
%A Atzmueller, Martin
%A Kniewel, Romy
%A Hoberg, Sebastian
%A Stumme, Gerd
%A Schmidt, Ludger
%B GfA-Frühjahrskongress
%C Chemnitz
%D 2011
%T Gestaltung technisch-sozialer Vernetzung in der Arbeitsorganisation: Untersuchung zur Nutzerakzeptanz von RFID-Technologie - 1.Atzmueller, M., Hotho, A., Strohmaier, M., Chin, A. eds.: Analysis of Social Media and Ubiquitous Data - International Workshops MSM 2010, Toronto, Canada, June 13, 2010, and MUSE 2010, Barcelona, Spain, September 20, 2010, Revised Selected Papers. Springer (2011).
@proceedings{conf/ht/2010msmmuse,
booktitle = {MSM/MUSE},
editor = {Atzmueller, Martin and Hotho, Andreas and Strohmaier, Markus and Chin, Alvin},
keywords = {media},
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series = {Lecture Notes in Computer Science},
title = {Analysis of Social Media and Ubiquitous Data - International Workshops MSM 2010, Toronto, Canada, June 13, 2010, and MUSE 2010, Barcelona, Spain, September 20, 2010, Revised Selected Papers},
volume = 6904,
year = 2011
}%0 Conference Proceedings
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%E Atzmueller, Martin
%E Hotho, Andreas
%E Strohmaier, Markus
%E Chin, Alvin
%I Springer
%T Analysis of Social Media and Ubiquitous Data - International Workshops MSM 2010, Toronto, Canada, June 13, 2010, and MUSE 2010, Barcelona, Spain, September 20, 2010, Revised Selected Papers
%U http://dblp.uni-trier.de/db/conf/ht/msmmuse2010.html
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%@ 978-3-642-23598-6 - 1.Illig, J., Hotho, A., Jäschke, R., Stumme, G.: A Comparison of Content-Based Tag Recommendations in Folksonomy Systems. In: Wolff, K., Palchunov, D., Zagoruiko, N., and Andelfinger, U. (eds.) Knowledge Processing and Data Analysis. pp. 136–149. Springer Berlin / Heidelberg (2011).Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset.
@incollection{springerlink:10.1007/978-3-642-22140-8_9,
abstract = {Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset.},
author = {Illig, Jens and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
booktitle = {Knowledge Processing and Data Analysis},
editor = {Wolff, Karl and Palchunov, Dmitry and Zagoruiko, Nikolay and Andelfinger, Urs},
keywords = {content},
note = {10.1007/978-3-642-22140-8_9},
pages = {136-149},
publisher = {Springer Berlin / Heidelberg},
series = {Lecture Notes in Computer Science},
title = {A Comparison of Content-Based Tag Recommendations in Folksonomy Systems},
volume = 6581,
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}%0 Book Section
%1 springerlink:10.1007/978-3-642-22140-8_9
%A Illig, Jens
%A Hotho, Andreas
%A Jäschke, Robert
%A Stumme, Gerd
%B Knowledge Processing and Data Analysis
%D 2011
%E Wolff, Karl
%E Palchunov, Dmitry
%E Zagoruiko, Nikolay
%E Andelfinger, Urs
%I Springer Berlin / Heidelberg
%P 136-149
%T A Comparison of Content-Based Tag Recommendations in Folksonomy Systems
%U http://dx.doi.org/10.1007/978-3-642-22140-8_9
%V 6581
%X Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset.
%@ 978-3-642-22139-2 - 1.Burke, R., Gemmell, J., Hotho, A., Jäschke, R.: Recommendation in the Social Web. AI Magazine. 32, 46–56 (2011).Recommender systems are a means of personalizing the presentation of information to ensure that users see the items most relevant to them. The social web has added new dimensions to the way people interact on the Internet, placing the emphasis on user-generated content. Users in social networks create photos, videos and other artifacts, collaborate with other users, socialize with their friends and share their opinions online. This outpouring of material has brought increased attention to recommender systems, as a means of managing this vast universe of content. At the same time, the diversity and complexity of the data has meant new challenges for researchers in recommendation. This article describes the nature of recommendation research in social web applications and provides some illustrative examples of current research directions and techniques. It is difficult to overstate the impact of the social web. This new breed of social applications is reshaping nearly every human activity from the way people watch movies to how they overthrow governments. Facebook allows its members to maintain friendships whether they live next door or on another continent. With Twitter, users from celebrities to ordinary folks can launch their 140 character messages out to a diverse horde of ‘‘followers.” Flickr and YouTube users upload their personal media to share with the world, while Wikipedia editors collaborate on the world’s largest encyclopedia.
@article{burke2011recommendation,
abstract = {Recommender systems are a means of personalizing the presentation of information to ensure that users see the items most relevant to them. The social web has added new dimensions to the way people interact on the Internet, placing the emphasis on user-generated content. Users in social networks create photos, videos and other artifacts, collaborate with other users, socialize with their friends and share their opinions online. This outpouring of material has brought increased attention to recommender systems, as a means of managing this vast universe of content. At the same time, the diversity and complexity of the data has meant new challenges for researchers in recommendation. This article describes the nature of recommendation research in social web applications and provides some illustrative examples of current research directions and techniques. It is difficult to overstate the impact of the social web. This new breed of social applications is reshaping nearly every human activity from the way people watch movies to how they overthrow governments. Facebook allows its members to maintain friendships whether they live next door or on another continent. With Twitter, users from celebrities to ordinary folks can launch their 140 character messages out to a diverse horde of ‘‘followers.” Flickr and YouTube users upload their personal media to share with the world, while Wikipedia editors collaborate on the world’s largest encyclopedia.},
author = {Burke, Robin and Gemmell, Jonathan and Hotho, Andreas and Jäschke, Robert},
journal = {AI Magazine},
keywords = {recommender},
number = 3,
pages = {46--56},
publisher = {Association for the Advancement of Artificial Intelligence},
title = {Recommendation in the Social Web},
volume = 32,
year = 2011
}%0 Journal Article
%1 burke2011recommendation
%A Burke, Robin
%A Gemmell, Jonathan
%A Hotho, Andreas
%A Jäschke, Robert
%D 2011
%I Association for the Advancement of Artificial Intelligence
%J AI Magazine
%N 3
%P 46--56
%T Recommendation in the Social Web
%U http://www.aaai.org/ojs/index.php/aimagazine/article/view/2373
%V 32
%X Recommender systems are a means of personalizing the presentation of information to ensure that users see the items most relevant to them. The social web has added new dimensions to the way people interact on the Internet, placing the emphasis on user-generated content. Users in social networks create photos, videos and other artifacts, collaborate with other users, socialize with their friends and share their opinions online. This outpouring of material has brought increased attention to recommender systems, as a means of managing this vast universe of content. At the same time, the diversity and complexity of the data has meant new challenges for researchers in recommendation. This article describes the nature of recommendation research in social web applications and provides some illustrative examples of current research directions and techniques. It is difficult to overstate the impact of the social web. This new breed of social applications is reshaping nearly every human activity from the way people watch movies to how they overthrow governments. Facebook allows its members to maintain friendships whether they live next door or on another continent. With Twitter, users from celebrities to ordinary folks can launch their 140 character messages out to a diverse horde of ‘‘followers.” Flickr and YouTube users upload their personal media to share with the world, while Wikipedia editors collaborate on the world’s largest encyclopedia. - 1.Atzmüller, M., Benz, D., Hotho, A., Stumme, G.: Towards Mining Semantic Maturity in Social Bookmarking Systems. In: Passant, A., Fernández, S., Breslin, J., and Bojārs, U. (eds.) Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011) (2011).
@inproceedings{atzmueller2011towards,
author = {Atzmüller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011)},
editor = {Passant, Alexandre and Fernández, Sergio and Breslin, John and Bojārs, Uldis},
keywords = {itegpub},
title = {Towards Mining Semantic Maturity in Social Bookmarking Systems},
year = 2011
}%0 Conference Paper
%1 atzmueller2011towards
%A Atzmüller, Martin
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011)
%D 2011
%E Passant, Alexandre
%E Fernández, Sergio
%E Breslin, John
%E Bojārs, Uldis
%T Towards Mining Semantic Maturity in Social Bookmarking Systems
%U https://www.kde.cs.uni-kassel.de/pub/pdf/atzmueller2011towards.pdf - 1.Kartal, A., Doerfel, S., Roßnagel, A., Stumme, G.: Privatsphären- und Datenschutz in Community-Plattformen: Gestaltung von Online-Bewertungsportalen. In: Heiß, H.-U., Pepper, P., Schlingloff, H., and Schneider, J. (eds.) Informatik 2011 - Informatik schafft Communities - Proceedings der 41. GI-Jahrestagung. p. 412. Bonner Köllen Verlag (2011).Aufgrund der mittlerweile unüberschaubaren Vielfalt von Anwendungsmöglichkeiten des Web 2.0, findet man fast zu jedem Lebensbereich eine passende Community im Netz. Dabei steigt auch die Anzahl der Bewertungsportale stetig und betrifft längst nicht mehr nur die Bewertung von Waren, sondern erstreckt sich unterdessen auch auf Beurteilungen von Leistungen und Eigenschaften von zu bestimmten Berufsgruppen gehörenden Personen. Diese Entwicklung birgt die Gefahr, dass die dadurch gewonnenen persönlichen Daten durchaus geeignet sind, wahrheitswidrig ein übermäßig positives oder übermäßig negatives Persönlichkeitsbild des Betroffenen zu konstruieren und dadurch sein Ansehen zu beeinflussen. Im Hinblick auf Fragen im Zusammenhang mit dem Persönlichkeits- und Datenschutz soll der folgende Beitrag Maßstäbe an eine verfassungs- und datenschutzkonforme technische Gestaltung von Online-Bewertungsportalen aufzeigen.
@inproceedings{kartal2011privatsphren,
abstract = {Aufgrund der mittlerweile unüberschaubaren Vielfalt von Anwendungsmöglichkeiten des Web 2.0, findet man fast zu jedem Lebensbereich eine passende Community im Netz. Dabei steigt auch die Anzahl der Bewertungsportale stetig und betrifft längst nicht mehr nur die Bewertung von Waren, sondern erstreckt sich unterdessen auch auf Beurteilungen von Leistungen und Eigenschaften von zu bestimmten Berufsgruppen gehörenden Personen. Diese Entwicklung birgt die Gefahr, dass die dadurch gewonnenen persönlichen Daten durchaus geeignet sind, wahrheitswidrig ein übermäßig positives oder übermäßig negatives Persönlichkeitsbild des Betroffenen zu konstruieren und dadurch sein Ansehen zu beeinflussen. Im Hinblick auf Fragen im Zusammenhang mit dem Persönlichkeits- und Datenschutz soll der folgende Beitrag Maßstäbe an eine verfassungs- und datenschutzkonforme technische Gestaltung von Online-Bewertungsportalen aufzeigen.},
author = {Kartal, Aliye and Doerfel, Stephan and Roßnagel, Alexander and Stumme, Gerd},
booktitle = {Informatik 2011 - Informatik schafft Communities - Proceedings der 41. GI-Jahrestagung},
editor = {Heiß, Hans-Ulrich and Pepper, Peter and Schlingloff, Holger and Schneider, Jörg},
keywords = {itegpub},
month = 10,
organization = {Gesellschaft für Informatik e.V. (GI)},
pages = 412,
publisher = {Bonner Köllen Verlag},
series = {Lecture Notes in Informatics},
title = {Privatsphären- und Datenschutz in Community-Plattformen: Gestaltung von Online-Bewertungsportalen},
volume = 192,
year = 2011
}%0 Conference Paper
%1 kartal2011privatsphren
%A Kartal, Aliye
%A Doerfel, Stephan
%A Roßnagel, Alexander
%A Stumme, Gerd
%B Informatik 2011 - Informatik schafft Communities - Proceedings der 41. GI-Jahrestagung
%D 2011
%E Heiß, Hans-Ulrich
%E Pepper, Peter
%E Schlingloff, Holger
%E Schneider, Jörg
%I Bonner Köllen Verlag
%P 412
%T Privatsphären- und Datenschutz in Community-Plattformen: Gestaltung von Online-Bewertungsportalen
%U http://www.informatik2011.de/541.html
%V 192
%X Aufgrund der mittlerweile unüberschaubaren Vielfalt von Anwendungsmöglichkeiten des Web 2.0, findet man fast zu jedem Lebensbereich eine passende Community im Netz. Dabei steigt auch die Anzahl der Bewertungsportale stetig und betrifft längst nicht mehr nur die Bewertung von Waren, sondern erstreckt sich unterdessen auch auf Beurteilungen von Leistungen und Eigenschaften von zu bestimmten Berufsgruppen gehörenden Personen. Diese Entwicklung birgt die Gefahr, dass die dadurch gewonnenen persönlichen Daten durchaus geeignet sind, wahrheitswidrig ein übermäßig positives oder übermäßig negatives Persönlichkeitsbild des Betroffenen zu konstruieren und dadurch sein Ansehen zu beeinflussen. Im Hinblick auf Fragen im Zusammenhang mit dem Persönlichkeits- und Datenschutz soll der folgende Beitrag Maßstäbe an eine verfassungs- und datenschutzkonforme technische Gestaltung von Online-Bewertungsportalen aufzeigen. - 1.Jäschke, R.: Formal Concept Analysis and Tag Recommendations in Collaborative Tagging Systems. Akademische Verlagsgesellschaft AKA, Heidelberg, Germany (2011).One of the most noticeable innovation that emerged with the advent of the Web 2.0 and the focal point of this thesis are collaborative tagging systems. They allow users to annotate arbitrary resources with freely chosen keywords, so called tags. The tags are used for navigation, finding resources, and serendipitous browsing and thus provide an immediate benefit for the user. By now, several systems for tagging photos, web links, publication references, videos, etc. have attracted millions of users which in turn annotated countless resources. Tagging gained so much popularity that it spread into other applications like web browsers, software packet managers, and even file systems. Therefore, the relevance of the methods presented in this thesis goes beyond the Web 2.0. The conceptual structure underlying collaborative tagging systems is called folksonomy. It can be represented as a tripartite hypergraph with user, tag, and resource nodes. Each edge of the graph expresses the fact that a user annotated a resource with a tag. This social network constitutes a lightweight conceptual structure that is not formalized, but rather implicit and thus needs to be extracted with knowledge discovery methods. In this thesis a new data mining task – the mining of all frequent tri-concepts – is presented, together with an efficient algorithm for discovering such implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. Extending the theory of triadic Formal Concept Analysis, we provide a formal definition of the problem, and present an efficient algorithm for its solution. We show the applicability of our approach on three large real-world examples and thereby perform a conceptual clustering of two collaborative tagging systems. Finally, we introduce neighborhoods of triadic concepts as basis for a lightweight visualization of tri-lattices. The social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind, has been developed by our research group. Besides being a useful tool for many scientists, it provides interested researchers a basis for the evaluation and integration of their knowledge discovery methods. This thesis introduces BibSonomy as an exemplary collaborative tagging system and gives an overview of its architecture and some of its features. Furthermore, BibSonomy is used as foundation for evaluating and integrating some of the discussed approaches. Collaborative tagging systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In this thesis we evaluate and compare several recommendation algorithms on large-scale real-world datasets: an adaptation of user-based Collaborative Filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag co-occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag co-occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We demonstrate how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender. Furthermore, we show how to integrate recommendation methods into a real tagging system, record and evaluate their performance by describing the tag recommendation framework we developed for BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. We also present an evaluation of the framework which demonstrates its power. The folksonomy graph shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Clicklogs of web search engines can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large folksonomy snapshot and on query logs of two large search engines. We find that all of the three datasets exhibit similar structural properties and thus conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of collaborative tagging users is driven by similar dynamics. In this thesis we further transfer the folksonomy paradigm to the Social Semantic Desktop – a new model of computer desktop that uses Semantic Web technologies to better link information items. There we apply community support methods to the folksonomy found in the network of social semantic desktops. Thus, we connect knowledge discovery for folksonomies with semantic technologies. Alltogether, the research in this thesis is centered around collaborative tagging systems and their underlying datastructure – folksonomies – and thereby paves the way for the further dissemination of this successful knowledge management paradigm.
@book{jaeschke2011formal,
abstract = {One of the most noticeable innovation that emerged with the advent of the Web 2.0 and the focal point of this thesis are collaborative tagging systems. They allow users to annotate arbitrary resources with freely chosen keywords, so called tags. The tags are used for navigation, finding resources, and serendipitous browsing and thus provide an immediate benefit for the user. By now, several systems for tagging photos, web links, publication references, videos, etc. have attracted millions of users which in turn annotated countless resources. Tagging gained so much popularity that it spread into other applications like web browsers, software packet managers, and even file systems. Therefore, the relevance of the methods presented in this thesis goes beyond the Web 2.0. The conceptual structure underlying collaborative tagging systems is called folksonomy. It can be represented as a tripartite hypergraph with user, tag, and resource nodes. Each edge of the graph expresses the fact that a user annotated a resource with a tag. This social network constitutes a lightweight conceptual structure that is not formalized, but rather implicit and thus needs to be extracted with knowledge discovery methods. In this thesis a new data mining task – the mining of all frequent tri-concepts – is presented, together with an efficient algorithm for discovering such implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. Extending the theory of triadic Formal Concept Analysis, we provide a formal definition of the problem, and present an efficient algorithm for its solution. We show the applicability of our approach on three large real-world examples and thereby perform a conceptual clustering of two collaborative tagging systems. Finally, we introduce neighborhoods of triadic concepts as basis for a lightweight visualization of tri-lattices. The social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind, has been developed by our research group. Besides being a useful tool for many scientists, it provides interested researchers a basis for the evaluation and integration of their knowledge discovery methods. This thesis introduces BibSonomy as an exemplary collaborative tagging system and gives an overview of its architecture and some of its features. Furthermore, BibSonomy is used as foundation for evaluating and integrating some of the discussed approaches. Collaborative tagging systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In this thesis we evaluate and compare several recommendation algorithms on large-scale real-world datasets: an adaptation of user-based Collaborative Filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag co-occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag co-occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We demonstrate how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender. Furthermore, we show how to integrate recommendation methods into a real tagging system, record and evaluate their performance by describing the tag recommendation framework we developed for BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. We also present an evaluation of the framework which demonstrates its power. The folksonomy graph shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Clicklogs of web search engines can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large folksonomy snapshot and on query logs of two large search engines. We find that all of the three datasets exhibit similar structural properties and thus conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of collaborative tagging users is driven by similar dynamics. In this thesis we further transfer the folksonomy paradigm to the Social Semantic Desktop – a new model of computer desktop that uses Semantic Web technologies to better link information items. There we apply community support methods to the folksonomy found in the network of social semantic desktops. Thus, we connect knowledge discovery for folksonomies with semantic technologies. Alltogether, the research in this thesis is centered around collaborative tagging systems and their underlying datastructure – folksonomies – and thereby paves the way for the further dissemination of this successful knowledge management paradigm.},
address = {Heidelberg, Germany},
author = {Jäschke, Robert},
keywords = {recommender},
month = {01},
publisher = {Akademische Verlagsgesellschaft AKA},
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%X One of the most noticeable innovation that emerged with the advent of the Web 2.0 and the focal point of this thesis are collaborative tagging systems. They allow users to annotate arbitrary resources with freely chosen keywords, so called tags. The tags are used for navigation, finding resources, and serendipitous browsing and thus provide an immediate benefit for the user. By now, several systems for tagging photos, web links, publication references, videos, etc. have attracted millions of users which in turn annotated countless resources. Tagging gained so much popularity that it spread into other applications like web browsers, software packet managers, and even file systems. Therefore, the relevance of the methods presented in this thesis goes beyond the Web 2.0. The conceptual structure underlying collaborative tagging systems is called folksonomy. It can be represented as a tripartite hypergraph with user, tag, and resource nodes. Each edge of the graph expresses the fact that a user annotated a resource with a tag. This social network constitutes a lightweight conceptual structure that is not formalized, but rather implicit and thus needs to be extracted with knowledge discovery methods. In this thesis a new data mining task – the mining of all frequent tri-concepts – is presented, together with an efficient algorithm for discovering such implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. Extending the theory of triadic Formal Concept Analysis, we provide a formal definition of the problem, and present an efficient algorithm for its solution. We show the applicability of our approach on three large real-world examples and thereby perform a conceptual clustering of two collaborative tagging systems. Finally, we introduce neighborhoods of triadic concepts as basis for a lightweight visualization of tri-lattices. The social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind, has been developed by our research group. Besides being a useful tool for many scientists, it provides interested researchers a basis for the evaluation and integration of their knowledge discovery methods. This thesis introduces BibSonomy as an exemplary collaborative tagging system and gives an overview of its architecture and some of its features. Furthermore, BibSonomy is used as foundation for evaluating and integrating some of the discussed approaches. Collaborative tagging systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In this thesis we evaluate and compare several recommendation algorithms on large-scale real-world datasets: an adaptation of user-based Collaborative Filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag co-occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag co-occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We demonstrate how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender. Furthermore, we show how to integrate recommendation methods into a real tagging system, record and evaluate their performance by describing the tag recommendation framework we developed for BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. We also present an evaluation of the framework which demonstrates its power. The folksonomy graph shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Clicklogs of web search engines can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large folksonomy snapshot and on query logs of two large search engines. We find that all of the three datasets exhibit similar structural properties and thus conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of collaborative tagging users is driven by similar dynamics. In this thesis we further transfer the folksonomy paradigm to the Social Semantic Desktop – a new model of computer desktop that uses Semantic Web technologies to better link information items. There we apply community support methods to the folksonomy found in the network of social semantic desktops. Thus, we connect knowledge discovery for folksonomies with semantic technologies. Alltogether, the research in this thesis is centered around collaborative tagging systems and their underlying datastructure – folksonomies – and thereby paves the way for the further dissemination of this successful knowledge management paradigm.
%@ 978-3-89838-332-5 - 1.Atzmueller, M., Benz, D., Doerfel, S., Hotho, A., Jäschke, R., Macek, B.E., Mitzlaff, F., Scholz, C., Stumme, G.: Enhancing Social Interactions at Conferences. it - Information Technology. 53, 101–107 (2011). https://doi.org/10.1524/itit.2011.0631.
@article{martin2011enhancing,
author = {Atzmueller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Bjoern Elmar and Mitzlaff, Folke and Scholz, Christoph and Stumme, Gerd},
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%A Doerfel, Stephan
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%A Macek, Bjoern Elmar
%A Mitzlaff, Folke
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%A Stumme, Gerd
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%V 53 - 1.Valtchev, P., Jäschke, R. eds.: Formal Concept Analysis. Springer, Berlin/Heidelberg (2011). https://doi.org/10.1007/978-3-642-20514-9_2.The present volume features a selection of the papers presented at the 9th International Conference on Formal Concept Analysis (ICFCA 2011). Over the years, the ICFCA conference series has grown into the premier forum for dissemination of research on topics from formal concept analysis (FCA) theory and applications, as well as from the related fields of lattices and partially ordered structures. FCA is a multi-disciplinary field with strong roots in the mathematical theory of partial orders and lattices, with tools originating in computer science and artificial intelligence. FCA emerged in the early 1980s from efforts to restructure lattice theory to promote better communication between lattice theorists and potential users of lattice-based methods for data management. Initially, the central theme was the mathematical formalization of concept and conceptual hierarchy. Since then, the field has developed into a constantly growing research area in its own right with a thriving theoretical community and an increasing number of applications in data and knowledge processing including disciplines such as data visualization, information retrieval, machine learning, software engineering, data analysis, data mining, social networks analysis, etc. ICFCA 2011 was held from May 2 to May 6, 2011, in Nicosia, Cyprus. The program committee received 49 high-quality submissions that were subjected to a highly competitive selection process. Each paper was reviewed by three referees (exceptionally two or four). After a first round, some papers got a definitive acceptance status, while others got accepted conditionally to improvements in their content. The latter got to a second round of reviewing. The overall outcome was the acceptance of 16 papers as regular ones for presentation at the conference and publication in this volume. Another seven papers have still been assessed as valuable for discussion at the conference and were therefore collected in the supplementary proceedings. The regular papers presented hereafter cover advances on a wide range of subjects from FCA and related fields. A first group of papers tackled mathematical problems within the FCA field. A subset thereof focused on factor identification within the incidence relation or its lattice representation (papers by Glodeanu and by Krupka). The remainder of the group proposed characterizations of particular classes of ordered structures (papers by Doerfel and by Meschke et al.). A second group of papers addressed algorithmic problems from FCA and related fields. Two papers approached their problems from an algorithmic complexity viewpoint (papers by Distel and by Babin and Kuznetsov) while the final paper in this group addressed algorithmic problems for general lattices, i.e., not represented as formal contexts, with an FCA-based approach (work by Balcázar and Tîrnăucă). A third group studied alternative approaches for extending the expressive power of the core FCA, e.g., by generalizing the standard one-valued attributes to attributes valued in algebraic rings (work by González Calabozo et al.), by introducing pointer-like attributes, a.k.a. links (paper by Kötters), or by substituting set-shaped concept intents with modal logic expressions (paper by Soldano and Ventos). A fourth group focused on data mining-oriented aspects of FCA: agreement lattices in structured data mining (paper by Nedjar et al.), triadic association rule mining (work by Missaoui and Kwuida) and bi-clustering of numerical data (Kaytoue et al.). An addional paper shed some initial light on a key aspect of FCA-based data analysis and mining, i.e., the filtering of interesting concepts (paper by Belohlavek and Macko). Finally, a set of exciting applications of both basic and enhanced FCA frameworks to practical problems have beed described: in analysis of gene expression data (the already mentioned work by González Calabozo et al.), in web services composition (paper by Azmeh et al.) and in browsing and retrieval of structured data (work by Wray and Eklund). This volume also contains three keynote papers submitted by the invited speakers of the conference. All these contributions constitute a volume of high quality which is the result of the hard work done by the authors, the invited speakers and the reviewers. We therefore wish to thank the members of the Program Committee and of the Editorial Board whose steady involvement and professionalism helped a lot. We would also like to acknowledge the participation of all the external reviewers who sent many valuable comments. Kudos also go to EasyChair for having made the reviewing/editing process a real pleasure. Special thanks go to the Cyprus Tourism Organisation for sponsoring the conference and to the University of Nicosia for hosting it. Finally we wish to thank the Conference Chair Florent Domenach and his colleagues from the Organization Committee for the mountains of energy they put behind the conference organization process right from the beginning in order to make it a total success. We would also like to express our gratitude towards Dr. Peristianis, President of the University of Nicosia, for his personal support.
@proceedings{valtchev2011formal,
abstract = {The present volume features a selection of the papers presented at the 9th International Conference on Formal Concept Analysis (ICFCA 2011). Over the years, the ICFCA conference series has grown into the premier forum for dissemination of research on topics from formal concept analysis (FCA) theory and applications, as well as from the related fields of lattices and partially ordered structures. FCA is a multi-disciplinary field with strong roots in the mathematical theory of partial orders and lattices, with tools originating in computer science and artificial intelligence. FCA emerged in the early 1980s from efforts to restructure lattice theory to promote better communication between lattice theorists and potential users of lattice-based methods for data management. Initially, the central theme was the mathematical formalization of concept and conceptual hierarchy. Since then, the field has developed into a constantly growing research area in its own right with a thriving theoretical community and an increasing number of applications in data and knowledge processing including disciplines such as data visualization, information retrieval, machine learning, software engineering, data analysis, data mining, social networks analysis, etc. ICFCA 2011 was held from May 2 to May 6, 2011, in Nicosia, Cyprus. The program committee received 49 high-quality submissions that were subjected to a highly competitive selection process. Each paper was reviewed by three referees (exceptionally two or four). After a first round, some papers got a definitive acceptance status, while others got accepted conditionally to improvements in their content. The latter got to a second round of reviewing. The overall outcome was the acceptance of 16 papers as regular ones for presentation at the conference and publication in this volume. Another seven papers have still been assessed as valuable for discussion at the conference and were therefore collected in the supplementary proceedings. The regular papers presented hereafter cover advances on a wide range of subjects from FCA and related fields. A first group of papers tackled mathematical problems within the FCA field. A subset thereof focused on factor identification within the incidence relation or its lattice representation (papers by Glodeanu and by Krupka). The remainder of the group proposed characterizations of particular classes of ordered structures (papers by Doerfel and by Meschke et al.). A second group of papers addressed algorithmic problems from FCA and related fields. Two papers approached their problems from an algorithmic complexity viewpoint (papers by Distel and by Babin and Kuznetsov) while the final paper in this group addressed algorithmic problems for general lattices, i.e., not represented as formal contexts, with an FCA-based approach (work by Balcázar and Tîrnăucă). A third group studied alternative approaches for extending the expressive power of the core FCA, e.g., by generalizing the standard one-valued attributes to attributes valued in algebraic rings (work by González Calabozo et al.), by introducing pointer-like attributes, a.k.a. links (paper by Kötters), or by substituting set-shaped concept intents with modal logic expressions (paper by Soldano and Ventos). A fourth group focused on data mining-oriented aspects of FCA: agreement lattices in structured data mining (paper by Nedjar et al.), triadic association rule mining (work by Missaoui and Kwuida) and bi-clustering of numerical data (Kaytoue et al.). An addional paper shed some initial light on a key aspect of FCA-based data analysis and mining, i.e., the filtering of interesting concepts (paper by Belohlavek and Macko). Finally, a set of exciting applications of both basic and enhanced FCA frameworks to practical problems have beed described: in analysis of gene expression data (the already mentioned work by González Calabozo et al.), in web services composition (paper by Azmeh et al.) and in browsing and retrieval of structured data (work by Wray and Eklund). This volume also contains three keynote papers submitted by the invited speakers of the conference. All these contributions constitute a volume of high quality which is the result of the hard work done by the authors, the invited speakers and the reviewers. We therefore wish to thank the members of the Program Committee and of the Editorial Board whose steady involvement and professionalism helped a lot. We would also like to acknowledge the participation of all the external reviewers who sent many valuable comments. Kudos also go to EasyChair for having made the reviewing/editing process a real pleasure. Special thanks go to the Cyprus Tourism Organisation for sponsoring the conference and to the University of Nicosia for hosting it. Finally we wish to thank the Conference Chair Florent Domenach and his colleagues from the Organization Committee for the mountains of energy they put behind the conference organization process right from the beginning in order to make it a total success. We would also like to express our gratitude towards Dr. Peristianis, President of the University of Nicosia, for his personal support.},
address = {Berlin/Heidelberg},
editor = {Valtchev, Petko and Jäschke, Robert},
keywords = {icfca},
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series = {Lecture Notes in Artificial Intelligence},
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%E Jäschke, Robert
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%U http://www.springer.com/computer/ai/book/978-3-642-20513-2
%V 6628
%X The present volume features a selection of the papers presented at the 9th International Conference on Formal Concept Analysis (ICFCA 2011). Over the years, the ICFCA conference series has grown into the premier forum for dissemination of research on topics from formal concept analysis (FCA) theory and applications, as well as from the related fields of lattices and partially ordered structures. FCA is a multi-disciplinary field with strong roots in the mathematical theory of partial orders and lattices, with tools originating in computer science and artificial intelligence. FCA emerged in the early 1980s from efforts to restructure lattice theory to promote better communication between lattice theorists and potential users of lattice-based methods for data management. Initially, the central theme was the mathematical formalization of concept and conceptual hierarchy. Since then, the field has developed into a constantly growing research area in its own right with a thriving theoretical community and an increasing number of applications in data and knowledge processing including disciplines such as data visualization, information retrieval, machine learning, software engineering, data analysis, data mining, social networks analysis, etc. ICFCA 2011 was held from May 2 to May 6, 2011, in Nicosia, Cyprus. The program committee received 49 high-quality submissions that were subjected to a highly competitive selection process. Each paper was reviewed by three referees (exceptionally two or four). After a first round, some papers got a definitive acceptance status, while others got accepted conditionally to improvements in their content. The latter got to a second round of reviewing. The overall outcome was the acceptance of 16 papers as regular ones for presentation at the conference and publication in this volume. Another seven papers have still been assessed as valuable for discussion at the conference and were therefore collected in the supplementary proceedings. The regular papers presented hereafter cover advances on a wide range of subjects from FCA and related fields. A first group of papers tackled mathematical problems within the FCA field. A subset thereof focused on factor identification within the incidence relation or its lattice representation (papers by Glodeanu and by Krupka). The remainder of the group proposed characterizations of particular classes of ordered structures (papers by Doerfel and by Meschke et al.). A second group of papers addressed algorithmic problems from FCA and related fields. Two papers approached their problems from an algorithmic complexity viewpoint (papers by Distel and by Babin and Kuznetsov) while the final paper in this group addressed algorithmic problems for general lattices, i.e., not represented as formal contexts, with an FCA-based approach (work by Balcázar and Tîrnăucă). A third group studied alternative approaches for extending the expressive power of the core FCA, e.g., by generalizing the standard one-valued attributes to attributes valued in algebraic rings (work by González Calabozo et al.), by introducing pointer-like attributes, a.k.a. links (paper by Kötters), or by substituting set-shaped concept intents with modal logic expressions (paper by Soldano and Ventos). A fourth group focused on data mining-oriented aspects of FCA: agreement lattices in structured data mining (paper by Nedjar et al.), triadic association rule mining (work by Missaoui and Kwuida) and bi-clustering of numerical data (Kaytoue et al.). An addional paper shed some initial light on a key aspect of FCA-based data analysis and mining, i.e., the filtering of interesting concepts (paper by Belohlavek and Macko). Finally, a set of exciting applications of both basic and enhanced FCA frameworks to practical problems have beed described: in analysis of gene expression data (the already mentioned work by González Calabozo et al.), in web services composition (paper by Azmeh et al.) and in browsing and retrieval of structured data (work by Wray and Eklund). This volume also contains three keynote papers submitted by the invited speakers of the conference. All these contributions constitute a volume of high quality which is the result of the hard work done by the authors, the invited speakers and the reviewers. We therefore wish to thank the members of the Program Committee and of the Editorial Board whose steady involvement and professionalism helped a lot. We would also like to acknowledge the participation of all the external reviewers who sent many valuable comments. Kudos also go to EasyChair for having made the reviewing/editing process a real pleasure. Special thanks go to the Cyprus Tourism Organisation for sponsoring the conference and to the University of Nicosia for hosting it. Finally we wish to thank the Conference Chair Florent Domenach and his colleagues from the Organization Committee for the mountains of energy they put behind the conference organization process right from the beginning in order to make it a total success. We would also like to express our gratitude towards Dr. Peristianis, President of the University of Nicosia, for his personal support.
%@ 978-3-642-20513-2 - 1.Benz, D., Körner, C., Hotho, A., Stumme, G., Strohmaier, M.: One Tag to Bind Them All : Measuring Term Abstractness in Social Metadata. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., Pan, J., and Leenheer, P.D. (eds.) Proceedings of the 8th Extended Semantic Web Conference (ESWC 2011). , Heraklion, Crete (2011).Recent research has demonstrated how the widespread adoption of collaborative tagging systems yields emergent semantics. In recent years, much has been learned about how to harvest the data produced by taggers for engineering light-weight ontologies. For example, existing measures of tag similarity and tag relatedness have proven crucial step stones for making latent semantic relations in tagging systems explicit. However, little progress has been made on other issues, such as understanding the different levels of tag generality (or tag abstractness), which is essential for, among others, identifying hierarchical relationships between concepts. In this paper we aim to address this gap. Starting from a review of linguistic definitions of word abstractness, we first use several large-scale ontologies and taxonomies as grounded measures of word generality, including Yago, Wordnet, DMOZ and Wikitaxonomy. Then, we introduce and apply several folksonomy-based methods to measure the level of generality of given tags. We evaluate these methods by comparing them with the grounded measures. Our results suggest that the generality of tags in social tagging systems can be approximated with simple measures. Our work has implications for a number of problems related to social tagging systems, including search, tag recommendation, and the acquisition of light-weight ontologies from tagging data.
@inproceedings{benz2011measuring,
abstract = {Recent research has demonstrated how the widespread adoption of collaborative tagging systems yields emergent semantics. In recent years, much has been learned about how to harvest the data produced by taggers for engineering light-weight ontologies. For example, existing measures of tag similarity and tag relatedness have proven crucial step stones for making latent semantic relations in tagging systems explicit. However, little progress has been made on other issues, such as understanding the different levels of tag generality (or tag abstractness), which is essential for, among others, identifying hierarchical relationships between concepts. In this paper we aim to address this gap. Starting from a review of linguistic definitions of word abstractness, we first use several large-scale ontologies and taxonomies as grounded measures of word generality, including Yago, Wordnet, DMOZ and Wikitaxonomy. Then, we introduce and apply several folksonomy-based methods to measure the level of generality of given tags. We evaluate these methods by comparing them with the grounded measures. Our results suggest that the generality of tags in social tagging systems can be approximated with simple measures. Our work has implications for a number of problems related to social tagging systems, including search, tag recommendation, and the acquisition of light-weight ontologies from tagging data.},
address = {Heraklion, Crete},
author = {Benz, Dominik and Körner, Christian and Hotho, Andreas and Stumme, Gerd and Strohmaier, Markus},
booktitle = {Proceedings of the 8th Extended Semantic Web Conference (ESWC 2011)},
editor = {Antoniou, Grigoris and Grobelnik, Marko and Simperl, Elena and Parsia, Bijan and Plexousakis, Dimitris and Pan, Jeff and Leenheer, Pieter De},
keywords = 2011,
month = {05},
title = {One Tag to Bind Them All : Measuring Term Abstractness in Social Metadata},
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}%0 Conference Paper
%1 benz2011measuring
%A Benz, Dominik
%A Körner, Christian
%A Hotho, Andreas
%A Stumme, Gerd
%A Strohmaier, Markus
%B Proceedings of the 8th Extended Semantic Web Conference (ESWC 2011)
%C Heraklion, Crete
%D 2011
%E Antoniou, Grigoris
%E Grobelnik, Marko
%E Simperl, Elena
%E Parsia, Bijan
%E Plexousakis, Dimitris
%E Pan, Jeff
%E Leenheer, Pieter De
%T One Tag to Bind Them All : Measuring Term Abstractness in Social Metadata
%U https://www.kde.cs.uni-kassel.de/pub/pdf/benz2011measuring.pdf
%X Recent research has demonstrated how the widespread adoption of collaborative tagging systems yields emergent semantics. In recent years, much has been learned about how to harvest the data produced by taggers for engineering light-weight ontologies. For example, existing measures of tag similarity and tag relatedness have proven crucial step stones for making latent semantic relations in tagging systems explicit. However, little progress has been made on other issues, such as understanding the different levels of tag generality (or tag abstractness), which is essential for, among others, identifying hierarchical relationships between concepts. In this paper we aim to address this gap. Starting from a review of linguistic definitions of word abstractness, we first use several large-scale ontologies and taxonomies as grounded measures of word generality, including Yago, Wordnet, DMOZ and Wikitaxonomy. Then, we introduce and apply several folksonomy-based methods to measure the level of generality of given tags. We evaluate these methods by comparing them with the grounded measures. Our results suggest that the generality of tags in social tagging systems can be approximated with simple measures. Our work has implications for a number of problems related to social tagging systems, including search, tag recommendation, and the acquisition of light-weight ontologies from tagging data. - 1.Atzmüller, M., Benz, D., Doerfel, S., Hotho, A., Jäschke, R., Macek, B.E., Mitzlaff, F., Scholz, C., Stumme, G.: Enhancing Social Interactions at Conferences. it - Information Technology. 53, 101–107 (2011). https://doi.org/10.1524/itit.2011.0631.
@article{martin2011enhancing,
author = {Atzmüller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Bjoern Elmar and Mitzlaff, Folke and Scholz, Christoph and Stumme, Gerd},
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%A Doerfel, Stephan
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%A Jäschke, Robert
%A Macek, Bjoern Elmar
%A Mitzlaff, Folke
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%V 53 - 1.Mitzlaff, F., Atzmueller, M., Benz, D., Hotho, A., Stumme, G.: Structure and Consistency: Assessment of Social Bookmarking Communities. In: Proceedings from Sunbelt XXXI. , Trade Winds Beach Resort (2011).
@inproceedings{mitzlaff2011social,
address = {Trade Winds Beach Resort},
author = {Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings from Sunbelt XXXI},
keywords = 2011,
title = {Structure and Consistency: Assessment of Social Bookmarking Communities},
year = 2011
}%0 Conference Paper
%1 mitzlaff2011social
%A Mitzlaff, Folke
%A Atzmueller, Martin
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings from Sunbelt XXXI
%C Trade Winds Beach Resort
%D 2011
%T Structure and Consistency: Assessment of Social Bookmarking Communities - 1.Mitzlaff, F., Atzmueller, M., Benz, D., Hotho, A., Stumme, G.: {Community Assessment using Evidence Networks}. In: Analysis of Social Media and Ubiquitous Data (2011).
@inproceedings{mitzlaff2011community,
author = {Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {Analysis of Social Media and Ubiquitous Data},
keywords = {itegpub},
series = {LNAI},
title = {{Community Assessment using Evidence Networks}},
volume = 6904,
year = 2011
}%0 Conference Paper
%1 mitzlaff2011community
%A Mitzlaff, Folke
%A Atzmueller, Martin
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Analysis of Social Media and Ubiquitous Data
%D 2011
%T {Community Assessment using Evidence Networks}
%V 6904 - 1.Scholz, C., Doerfel, S., Atzmueller, M., Hotho, A., Stumme, G.: Resource-Aware On-Line RFID Localization Using Proximity Data. In: Working Notes of the LWA 2011 - Learning, Knowledge, Adaptation (2011).
@inproceedings{scholz2011resourceaware,
author = {Scholz, Christoph and Doerfel, Stephan and Atzmueller, Martin and Hotho, Andreas and Stumme, Gerd},
booktitle = {Working Notes of the LWA 2011 - Learning, Knowledge, Adaptation},
keywords = {itegpub},
title = {Resource-Aware On-Line RFID Localization Using Proximity Data},
year = 2011
}%0 Conference Paper
%1 scholz2011resourceaware
%A Scholz, Christoph
%A Doerfel, Stephan
%A Atzmueller, Martin
%A Hotho, Andreas
%A Stumme, Gerd
%B Working Notes of the LWA 2011 - Learning, Knowledge, Adaptation
%D 2011
%T Resource-Aware On-Line RFID Localization Using Proximity Data - 1.Cattuto, C., Hotho, A.: Introduction to the Special Issue on Social Linking and Hypermedia. New Review of Hypermedia and Multimedia. 17, 241–242 (2011). https://doi.org/10.1080/13614568.2011.641407.
@article{doi:10.1080/13614568.2011.641407,
author = {Cattuto, Ciro and Hotho, Andreas},
journal = {New Review of Hypermedia and Multimedia},
keywords = 2011,
number = 3,
pages = {241-242},
title = {Introduction to the Special Issue on Social Linking and Hypermedia},
volume = 17,
year = 2011
}%0 Journal Article
%1 doi:10.1080/13614568.2011.641407
%A Cattuto, Ciro
%A Hotho, Andreas
%D 2011
%J New Review of Hypermedia and Multimedia
%N 3
%P 241-242
%R 10.1080/13614568.2011.641407
%T Introduction to the Special Issue on Social Linking and Hypermedia
%U http://www.tandfonline.com/doi/abs/10.1080/13614568.2011.641407
%V 17 - 1.Mitzlaff, F., Atzmueller, M., Stumme, G., Hotho, A.: {On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission)}. In: Proc. LWA 2013 (KDML Special Track). University of Bamberg, Bamberg, Germany (2011).
@inproceedings{mitzlaff2011semantics,
address = {Bamberg, Germany},
author = {Mitzlaff, Folke and Atzmueller, Martin and Stumme, Gerd and Hotho, Andreas},
booktitle = {Proc. LWA 2013 (KDML Special Track)},
keywords = {itegpub},
publisher = {University of Bamberg},
title = {{On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission)}},
year = 2011
}%0 Conference Paper
%1 mitzlaff2011semantics
%A Mitzlaff, Folke
%A Atzmueller, Martin
%A Stumme, Gerd
%A Hotho, Andreas
%B Proc. LWA 2013 (KDML Special Track)
%C Bamberg, Germany
%D 2011
%I University of Bamberg
%T {On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission)} - 1.Hotho, A., Stumme, G.: From Semantic Web Mining to Social and Ubiquitous Mining - A Subjective View on Past, Current, and Future Research. In: Fensel, D. (ed.) Foundations for the Web of Information and Services. pp. 143–153. Springer (2011).
@inproceedings{conf/birthday/HothoS11,
author = {Hotho, Andreas and Stumme, Gerd},
booktitle = {Foundations for the Web of Information and Services},
crossref = {conf/birthday/2011studer},
editor = {Fensel, Dieter},
keywords = 2011,
pages = {143-153},
publisher = {Springer},
title = {From Semantic Web Mining to Social and Ubiquitous Mining - A Subjective View on Past, Current, and Future Research.},
year = 2011
}%0 Conference Paper
%1 conf/birthday/HothoS11
%A Hotho, Andreas
%A Stumme, Gerd
%B Foundations for the Web of Information and Services
%D 2011
%E Fensel, Dieter
%I Springer
%P 143-153
%T From Semantic Web Mining to Social and Ubiquitous Mining - A Subjective View on Past, Current, and Future Research.
%U http://dblp.uni-trier.de/db/conf/birthday/studer2011.html#HothoS11
%@ 978-3-642-19796-3 - 1.Freyne, J., Anand, S.S., Guy, I., Hotho, A.: 3rd workshop on recommender systems and the social web. In: Proceedings of the fifth ACM conference on Recommender systems. pp. 383–384. ACM, Chicago, Illinois, USA (2011). https://doi.org/10.1145/2043932.2044014.The exponential growth of the social web poses challenges and new opportunities for recommender systems. The social web has turned information consumers into active contributors creating massive amounts of information. Finding relevant and interesting content at the right time and in the right context is challenging for existing recommender approaches. At the same time, social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation. The Social Web provides huge opportunities for recommender technology and in turn recommender technologies can play a part in fuelling the success of the Social Web phenomenon.
The goal of this one day workshop was to bring together researchers and practitioners to explore, discuss, and understand challenges and new opportunities for Recommender Systems and the Social Web. The workshop consisted both of technical sessions, in which selected participants presented their results or ongoing research, as well as informal breakout sessions on more focused topics.
Papers discussing various aspects of recommender system in the Social Web were submitted and selected for presentation and discussion in the workshop in a formal reviewing process: Case studies and novel fielded social recommender applications; Economy of community-based systems: Using recommenders to encourage users to contribute and sustain participation.; Social network and folksonomy development: Recommending friends, tags, bookmarks, blogs, music, communities etc.; Recommender systems mash-ups, Web 2.0 user interfaces, rich media recommender systems; Collaborative knowledge authoring, collective intelligence; Recommender applications involving users or groups directly in the recommendation process; Exploiting folksonomies, social network information, interaction, user context and communities or groups for recommendations; Trust and reputation aware social recommendations; Semantic Web recommender systems, use of ontologies or microformats; Empirical evaluation of social recommender techniques, success and failure measures
Full workshop details are available at http://www.dcs.warwick.ac.uk/~ssanand/RSWeb11/index.htm
@inproceedings{Freyne:2011:WRS:2043932.2044014,
abstract = {The exponential growth of the social web poses challenges and new opportunities for recommender systems. The social web has turned information consumers into active contributors creating massive amounts of information. Finding relevant and interesting content at the right time and in the right context is challenging for existing recommender approaches. At the same time, social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation. The Social Web provides huge opportunities for recommender technology and in turn recommender technologies can play a part in fuelling the success of the Social Web phenomenon.The goal of this one day workshop was to bring together researchers and practitioners to explore, discuss, and understand challenges and new opportunities for Recommender Systems and the Social Web. The workshop consisted both of technical sessions, in which selected participants presented their results or ongoing research, as well as informal breakout sessions on more focused topics.
Papers discussing various aspects of recommender system in the Social Web were submitted and selected for presentation and discussion in the workshop in a formal reviewing process: Case studies and novel fielded social recommender applications; Economy of community-based systems: Using recommenders to encourage users to contribute and sustain participation.; Social network and folksonomy development: Recommending friends, tags, bookmarks, blogs, music, communities etc.; Recommender systems mash-ups, Web 2.0 user interfaces, rich media recommender systems; Collaborative knowledge authoring, collective intelligence; Recommender applications involving users or groups directly in the recommendation process; Exploiting folksonomies, social network information, interaction, user context and communities or groups for recommendations; Trust and reputation aware social recommendations; Semantic Web recommender systems, use of ontologies or microformats; Empirical evaluation of social recommender techniques, success and failure measures
Full workshop details are available at http://www.dcs.warwick.ac.uk/~ssanand/RSWeb11/index.htm},
address = {New York, NY, USA},
author = {Freyne, Jill and Anand, Sarabjot Singh and Guy, Ido and Hotho, Andreas},
booktitle = {Proceedings of the fifth ACM conference on Recommender systems},
keywords = {cochair},
pages = {383--384},
publisher = {ACM},
series = {RecSys '11},
title = {3rd workshop on recommender systems and the social web},
year = 2011
}%0 Conference Paper
%1 Freyne:2011:WRS:2043932.2044014
%A Freyne, Jill
%A Anand, Sarabjot Singh
%A Guy, Ido
%A Hotho, Andreas
%B Proceedings of the fifth ACM conference on Recommender systems
%C New York, NY, USA
%D 2011
%I ACM
%P 383--384
%R 10.1145/2043932.2044014
%T 3rd workshop on recommender systems and the social web
%U http://doi.acm.org/10.1145/2043932.2044014
%X The exponential growth of the social web poses challenges and new opportunities for recommender systems. The social web has turned information consumers into active contributors creating massive amounts of information. Finding relevant and interesting content at the right time and in the right context is challenging for existing recommender approaches. At the same time, social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation. The Social Web provides huge opportunities for recommender technology and in turn recommender technologies can play a part in fuelling the success of the Social Web phenomenon.The goal of this one day workshop was to bring together researchers and practitioners to explore, discuss, and understand challenges and new opportunities for Recommender Systems and the Social Web. The workshop consisted both of technical sessions, in which selected participants presented their results or ongoing research, as well as informal breakout sessions on more focused topics.
Papers discussing various aspects of recommender system in the Social Web were submitted and selected for presentation and discussion in the workshop in a formal reviewing process: Case studies and novel fielded social recommender applications; Economy of community-based systems: Using recommenders to encourage users to contribute and sustain participation.; Social network and folksonomy development: Recommending friends, tags, bookmarks, blogs, music, communities etc.; Recommender systems mash-ups, Web 2.0 user interfaces, rich media recommender systems; Collaborative knowledge authoring, collective intelligence; Recommender applications involving users or groups directly in the recommendation process; Exploiting folksonomies, social network information, interaction, user context and communities or groups for recommendations; Trust and reputation aware social recommendations; Semantic Web recommender systems, use of ontologies or microformats; Empirical evaluation of social recommender techniques, success and failure measures
Full workshop details are available at http://www.dcs.warwick.ac.uk/~ssanand/RSWeb11/index.htm
%@ 978-1-4503-0683-6 - 1.{Björn-Elmar Macek, M.A.: Profile Mining in CVS-Logs and Face-to-Face Contacts for Recommending Software Developers. In: Proc. of the third Inernational Conference on Social Computing. pp. 250–257. IEEE Computer Society, Boston, MA, USA (2011).
@inproceedings{bjrnelmarmacek2011profile,
address = {Boston, MA, USA},
author = {{Björn-Elmar Macek, Martin Atzmueller, Gerd Stumme}},
booktitle = {Proc. of the third Inernational Conference on Social Computing},
keywords = {itegpub},
pages = {250 - 257},
publisher = {IEEE Computer Society},
title = {Profile Mining in CVS-Logs and Face-to-Face Contacts for Recommending Software Developers},
year = 2011
}%0 Conference Paper
%1 bjrnelmarmacek2011profile
%A {Björn-Elmar Macek, Martin Atzmueller
%B Proc. of the third Inernational Conference on Social Computing
%C Boston, MA, USA
%D 2011
%I IEEE Computer Society
%P 250 - 257
%T Profile Mining in CVS-Logs and Face-to-Face Contacts for Recommending Software Developers - 1.Krohn, M., Klein, N., Jandt, S., Atzmueller, M., Scholz, C., Hoffmann, H., Kniewel, R., Evers, C.: Das Forschungszentrum für Informationstechnik-Gestaltung (ITeG). Praxis der Informationsverarbeitung und Kommunikation. 34, 238–240 (2011).
@article{DBLP:journals/pik/KJASHKE11,
author = {Krohn, Michael and Klein, Niklas and Jandt, Silke and Atzmueller, Martin and Scholz, Christoph and Hoffmann, Holger and Kniewel, Romy and Evers, Christoph},
journal = {Praxis der Informationsverarbeitung und Kommunikation},
keywords = {itegpub},
number = 4,
pages = {238-240},
title = {Das Forschungszentrum für Informationstechnik-Gestaltung (ITeG)},
volume = 34,
year = 2011
}%0 Journal Article
%1 DBLP:journals/pik/KJASHKE11
%A Krohn, Michael
%A Klein, Niklas
%A Jandt, Silke
%A Atzmueller, Martin
%A Scholz, Christoph
%A Hoffmann, Holger
%A Kniewel, Romy
%A Evers, Christoph
%D 2011
%J Praxis der Informationsverarbeitung und Kommunikation
%N 4
%P 238-240
%T Das Forschungszentrum für Informationstechnik-Gestaltung (ITeG)
%V 34 - 1.Ackermann, M.R., Blömer, J., Scholz, C.: Hardness and Non-Approximability of Bregman Clustering Problems. Electronic Colloquium on Computational Complexity (ECCC). 18, 20 (2011).
@article{journals/eccc/TR11-015,
author = {Ackermann, Marcel R. and Blömer, Johannes and Scholz, Christoph},
journal = {Electronic Colloquium on Computational Complexity (ECCC)},
keywords = {k-median},
pages = 20,
title = {Hardness and Non-Approximability of Bregman Clustering Problems.},
volume = 18,
year = 2011
}%0 Journal Article
%1 journals/eccc/TR11-015
%A Ackermann, Marcel R.
%A Blömer, Johannes
%A Scholz, Christoph
%D 2011
%J Electronic Colloquium on Computational Complexity (ECCC)
%P 20
%T Hardness and Non-Approximability of Bregman Clustering Problems.
%U http://eccc.hpi-web.de/report/2011/015/
%V 18 - 1.Atzmueller, M., Hotho, A. eds.: {Proceedings of the 2011 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2011)}. ECML/PKDD 2011, Athens, Greece (2011).
@book{AH:11,
address = {Athens, Greece},
editor = {Atzmueller, Martin and Hotho, Andreas},
keywords = {muse},
publisher = {ECML/PKDD 2011},
title = {{Proceedings of the 2011 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2011)}},
year = 2011
}%0 Book
%1 AH:11
%C Athens, Greece
%D 2011
%E Atzmueller, Martin
%E Hotho, Andreas
%I ECML/PKDD 2011
%T {Proceedings of the 2011 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2011)} - 1.Navarro Bullock, B., Jäschke, R., Hotho, A.: Tagging data as implicit feedback for learning-to-rank. In: Proceedings of the ACM WebSci’11 (2011).
@inproceedings{bullock2011tagging,
author = {Navarro Bullock, Beate and Jäschke, Robert and Hotho, Andreas},
booktitle = {Proceedings of the ACM WebSci'11},
keywords = {logsonomy},
month = {06},
title = {Tagging data as implicit feedback for learning-to-rank},
year = 2011
}%0 Conference Paper
%1 bullock2011tagging
%A Navarro Bullock, Beate
%A Jäschke, Robert
%A Hotho, Andreas
%B Proceedings of the ACM WebSci'11
%D 2011
%T Tagging data as implicit feedback for learning-to-rank
%U http://journal.webscience.org/463/ - 1.Atzmueller, M., Benz, D., Hotho, A., Stumme, G.: Towards Mining Semantic Maturity in Social Bookmarking Systems. In: Passant, A., Fernández, S., Breslin, J., and Bojārs, U. (eds.) Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011) (2011).
@inproceedings{atzmueller2011towards,
author = {Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011)},
editor = {Passant, Alexandre and Fernández, Sergio and Breslin, John and Bojārs, Uldis},
keywords = {bookmarking},
title = {Towards Mining Semantic Maturity in Social Bookmarking Systems},
year = 2011
}%0 Conference Paper
%1 atzmueller2011towards
%A Atzmueller, Martin
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011)
%D 2011
%E Passant, Alexandre
%E Fernández, Sergio
%E Breslin, John
%E Bojārs, Uldis
%T Towards Mining Semantic Maturity in Social Bookmarking Systems
%U https://www.kde.cs.uni-kassel.de/pub/pdf/atzmueller2011towards.pdf - 1.Atzmueller, M.: Data Mining. In: McCarthy, P.M. and Boonthum, C. (eds.) Applied Natural Language Processing and Content Analysis: Advances in Identification, Investigation and Resolution. IGI Global (2011).
@incollection{Atzmueller:11,
author = {Atzmueller, Martin},
booktitle = {Applied Natural Language Processing and Content Analysis: Advances in Identification, Investigation and Resolution.},
editor = {McCarthy, Philip M. and Boonthum, Chutima},
keywords = {itegpub},
publisher = {IGI Global},
title = {Data Mining},
year = 2011
}%0 Book Section
%1 Atzmueller:11
%A Atzmueller, Martin
%B Applied Natural Language Processing and Content Analysis: Advances in Identification, Investigation and Resolution.
%D 2011
%E McCarthy, Philip M.
%E Boonthum, Chutima
%I IGI Global
%T Data Mining - 1.Bloehdorn, S., Blohm, S., Cimiano, P., Giesbrecht, E., Hotho, A., Lösch, U., Mädche, A., Mönch, E., Sorg, P., Staab, S., Völker, J.: Combining Data-Driven and Semantic Approaches for Text Mining. In: Fensel, D. (ed.) Foundations for the Web of Information and Services. pp. 115–142. Springer (2011).
@inproceedings{conf/birthday/BloehdornBCGHLMMSSV11,
author = {Bloehdorn, Stephan and Blohm, Sebastian and Cimiano, Philipp and Giesbrecht, Eugenie and Hotho, Andreas and Lösch, Uta and Mädche, Alexander and Mönch, Eddie and Sorg, Philipp and Staab, Steffen and Völker, Johanna},
booktitle = {Foundations for the Web of Information and Services},
crossref = {conf/birthday/2011studer},
editor = {Fensel, Dieter},
keywords = {text},
pages = {115-142},
publisher = {Springer},
title = {Combining Data-Driven and Semantic Approaches for Text Mining.},
year = 2011
}%0 Conference Paper
%1 conf/birthday/BloehdornBCGHLMMSSV11
%A Bloehdorn, Stephan
%A Blohm, Sebastian
%A Cimiano, Philipp
%A Giesbrecht, Eugenie
%A Hotho, Andreas
%A Lösch, Uta
%A Mädche, Alexander
%A Mönch, Eddie
%A Sorg, Philipp
%A Staab, Steffen
%A Völker, Johanna
%B Foundations for the Web of Information and Services
%D 2011
%E Fensel, Dieter
%I Springer
%P 115-142
%T Combining Data-Driven and Semantic Approaches for Text Mining.
%U http://dblp.uni-trier.de/db/conf/birthday/studer2011.html#BloehdornBCGHLMMSSV11
%@ 978-3-642-19796-3 - 1.Atzmueller, M., Doerfel, S., Hotho, A., Mitzlaff, F., Stumme, G.: Face-to-Face Contacts during LWA 2010 - Communities, Roles, and Key Players. In: Working Notes of the LWA 2011 - Learning, Knowledge, Adaptation (2011).
@inproceedings{atzmueller2011facetoface,
author = {Atzmueller, Martin and Doerfel, Stephan and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd},
booktitle = {Working Notes of the LWA 2011 - Learning, Knowledge, Adaptation},
keywords = {contacts},
title = {Face-to-Face Contacts during LWA 2010 - Communities, Roles, and Key Players},
year = 2011
}%0 Conference Paper
%1 atzmueller2011facetoface
%A Atzmueller, Martin
%A Doerfel, Stephan
%A Hotho, Andreas
%A Mitzlaff, Folke
%A Stumme, Gerd
%B Working Notes of the LWA 2011 - Learning, Knowledge, Adaptation
%D 2011
%T Face-to-Face Contacts during LWA 2010 - Communities, Roles, and Key Players - 1.Toepfer, M., Kluegl, P., Hotho, A., Puppe, F.: Segmentation of References with Skip-Chain Conditional Random Fields for Consistent Label Transitions. In: Workshop Notes of the LWA 2011 - Learning, Knowledge, Adaptation (2011).
@inproceedings{toepfer2011segmentation,
author = {Toepfer, Martin and Kluegl, Peter and Hotho, Andreas and Puppe, Frank},
booktitle = {Workshop Notes of the LWA 2011 - Learning, Knowledge, Adaptation},
keywords = {references},
title = {Segmentation of References with Skip-Chain Conditional Random Fields for Consistent Label Transitions},
year = 2011
}%0 Conference Paper
%1 toepfer2011segmentation
%A Toepfer, Martin
%A Kluegl, Peter
%A Hotho, Andreas
%A Puppe, Frank
%B Workshop Notes of the LWA 2011 - Learning, Knowledge, Adaptation
%D 2011
%T Segmentation of References with Skip-Chain Conditional Random Fields for Consistent Label Transitions
%U http://ki.informatik.uni-wuerzburg.de/papers/pkluegl/2011-LWA-SkYp.pdf - 1.Atzmueller, M., Doerfel, S., Hotho, A., Mitzlaff, F., Stumme, G.: Face-to-Face Contacts during a Conference: Communities, Roles, and Key Players. In: Proc. Workshop on Mining Ubiquitous and Social Environments (MUSE 2011) at ECML/PKDD 2011 (2011).
@inproceedings{atzmueller2011facetoface,
author = {Atzmueller, Martin and Doerfel, Stephan and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd},
booktitle = {Proc. Workshop on Mining Ubiquitous and Social Environments (MUSE 2011) at ECML/PKDD 2011},
keywords = {communities},
title = {Face-to-Face Contacts during a Conference: Communities, Roles, and Key Players},
year = 2011
}%0 Conference Paper
%1 atzmueller2011facetoface
%A Atzmueller, Martin
%A Doerfel, Stephan
%A Hotho, Andreas
%A Mitzlaff, Folke
%A Stumme, Gerd
%B Proc. Workshop on Mining Ubiquitous and Social Environments (MUSE 2011) at ECML/PKDD 2011
%D 2011
%T Face-to-Face Contacts during a Conference: Communities, Roles, and Key Players - 1.Atzmueller, M., Mitzlaff, F.: Efficient Descriptive Community Mining. In: Proc. 24th Intl. FLAIRS Conference. AAAI Press (2011).
@inproceedings{atzmueller2011efficient,
author = {Atzmueller, Martin and Mitzlaff, Folke},
booktitle = {Proc. 24th Intl. FLAIRS Conference},
keywords = {itegpub},
publisher = {AAAI Press},
title = {Efficient Descriptive Community Mining},
year = 2011
}%0 Conference Paper
%1 atzmueller2011efficient
%A Atzmueller, Martin
%A Mitzlaff, Folke
%B Proc. 24th Intl. FLAIRS Conference
%D 2011
%I AAAI Press
%T Efficient Descriptive Community Mining
2010
- 1.Mitzlaff, F., Atzmüller, M., Benz, D., Hotho, A., Stumme, G.: Community Assessment using Evidence Networks. In: Proceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010). , Barcelona, Spain (2010).Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well.
@inproceedings{mitzlaff2010community,
abstract = {Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well.},
address = {Barcelona, Spain},
author = {Mitzlaff, Folke and Atzmüller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010)},
keywords = {itegpub},
title = {Community Assessment using Evidence Networks},
year = 2010
}%0 Conference Paper
%1 mitzlaff2010community
%A Mitzlaff, Folke
%A Atzmüller, Martin
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010)
%C Barcelona, Spain
%D 2010
%T Community Assessment using Evidence Networks
%U https://www.kde.cs.uni-kassel.de/ws/muse2010
%X Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well. - 1.Atzmueller, M., Knauf, R., Bode, S., Farooq, Q.-U.-A., Riebisch, M. eds.: The IWK2010 Workshops: DERIS2010 and EMDT2010. Proceedings of the IWK2010 Workshops: International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS2010) and the First International Workshop on Evolution Support for Model-Based Development and Testing (EMDT2010). RWTH Aachen University (2010).
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series = {CEUR-WS},
title = {The IWK2010 Workshops: DERIS2010 and EMDT2010. Proceedings of the IWK2010 Workshops: International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS2010) and the First International Workshop on Evolution Support for Model-Based Development and Testing (EMDT2010)},
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%T The IWK2010 Workshops: DERIS2010 and EMDT2010. Proceedings of the IWK2010 Workshops: International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS2010) and the First International Workshop on Evolution Support for Model-Based Development and Testing (EMDT2010)
%V 646 - 1.Benz, D., Hotho, A., Jäschke, R., Krause, B., Mitzlaff, F., Schmitz, C., Stumme, G.: The Social Bookmark and Publication Management System {BibSonomy}. The VLDB Journal. 19, 849–875 (2010). https://doi.org/10.1007/s00778-010-0208-4.Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research.
@article{benz2010social,
abstract = {Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research.},
address = {Berlin/Heidelberg},
author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Mitzlaff, Folke and Schmitz, Christoph and Stumme, Gerd},
journal = {The VLDB Journal},
keywords = {bibsonomy},
month = 12,
number = 6,
pages = {849--875},
publisher = {Springer},
title = {The Social Bookmark and Publication Management System {BibSonomy}},
volume = 19,
year = 2010
}%0 Journal Article
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%A Benz, Dominik
%A Hotho, Andreas
%A Jäschke, Robert
%A Krause, Beate
%A Mitzlaff, Folke
%A Schmitz, Christoph
%A Stumme, Gerd
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%D 2010
%I Springer
%J The VLDB Journal
%N 6
%P 849--875
%R 10.1007/s00778-010-0208-4
%T The Social Bookmark and Publication Management System {BibSonomy}
%U https://www.kde.cs.uni-kassel.de/pub/pdf/benz2010social.pdf
%V 19
%X Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research. - 1.Atzmueller, M., Hotho, A. eds.: {Proceedings of the 2010 Workshop on Mining Ubiquitous and Social Environments (MUSE 2010)}. ECML/PKDD 2010, Barcelona, Spain (2010).
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%T {Proceedings of the 2010 Workshop on Mining Ubiquitous and Social Environments (MUSE 2010)} - 1.Benz, D., Hotho, A., Jäschke, R., Stumme, G., Halle, A., Lima-Gerlach, A.S., Steenweg, H., Stefani, S.: Academic Publication Management with PUMA - collect, organize and share publications. In: Proceedings of the 14. European Conference on Research and Advanced Technology for Digital Libraries. pp. 417–420 (2010). https://doi.org/10.1007.The PUMA project fosters the Open Access movement und aims at a better support of the researcher’s publication work. PUMA stands for an integrated solution, where the upload of a publication results automatically in an update of both the personal and institutional homepage, the creation of an entry in a social bookmarking systems like BibSonomy, an entry in the academic reporting system of the university, and its publication in the institutional repository. In this poster, we present the main features of our solution.
@inproceedings{Halle:2010,
abstract = {The PUMA project fosters the Open Access movement und aims at a better support of the researcher’s publication work. PUMA stands for an integrated solution, where the upload of a publication results automatically in an update of both the personal and institutional homepage, the creation of an entry in a social bookmarking systems like BibSonomy, an entry in the academic reporting system of the university, and its publication in the institutional repository. In this poster, we present the main features of our solution.},
author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd and Halle, Axel and Lima-Gerlach, Angela Sanches and Steenweg, Helge and Stefani, Sven},
booktitle = {Proceedings of the 14. European Conference on Research and Advanced Technology for Digital Libraries},
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title = {Academic Publication Management with PUMA - collect, organize and share publications},
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%@ 978-3-642-15464-5 - 1.Mitzlaff, F., Benz, D., Stumme, G., Hotho, A.: Visit me, click me, be my friend: an analysis of evidence networks of user relationships in BibSonomy. In: Proceedings of the 21st ACM conference on Hypertext and hypermedia. pp. 265–270. ACM, New York, NY, USA (2010).
@inproceedings{mitzlaff2010visit,
address = {New York, NY, USA},
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booktitle = {Proceedings of the 21st ACM conference on Hypertext and hypermedia},
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%I ACM
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%T Visit me, click me, be my friend: an analysis of evidence networks of user relationships in BibSonomy - 1.Körner, C., Benz, D., Hotho, A., Strohmaier, M., Stumme, G.: Social Bookmarking Systems: Verbosity Improves Semantics. In: Proceedings of INSNA Sunbelt XXX. , Riva del Garda Fierecongressi, Trento, Italy (2010).
@inproceedings{koerner2010social,
address = {Riva del Garda Fierecongressi, Trento, Italy},
author = {Körner, Christian and Benz, Dominik and Hotho, Andreas and Strohmaier, Markus and Stumme, Gerd},
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keywords = 2010,
title = {Social Bookmarking Systems: Verbosity Improves Semantics},
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}%0 Conference Paper
%1 koerner2010social
%A Körner, Christian
%A Benz, Dominik
%A Hotho, Andreas
%A Strohmaier, Markus
%A Stumme, Gerd
%B Proceedings of INSNA Sunbelt XXX
%C Riva del Garda Fierecongressi, Trento, Italy
%D 2010
%T Social Bookmarking Systems: Verbosity Improves Semantics - 1.Atzmueller, M., Benz, D., Hotho, A., Stumme, G. eds.: {Proceedings of the LWA 2010 - Lernen, Wissen, Adaptivität}. Department of Electrical Engineering/Computer Science, Kassel University (2010).
@book{ABHS:10,
editor = {Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
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%I Department of Electrical Engineering/Computer Science, Kassel University
%T {Proceedings of the LWA 2010 - Lernen, Wissen, Adaptivität} - 1.Atzmueller, M., Roth-Berghofer, T.: The Mining and Analysis Continuum of Explaining Uncovered. In: Proc. 30th SGAI International Conference on Artificial Intelligence (AI-2010) (2010).
@inproceedings{AR:10a,
author = {Atzmueller, Martin and Roth-Berghofer, Thomas},
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%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-mace-ai-2010.pdf - 1.Berendt, B., Krause, B., Kolbe-Nusser, S.: Intelligent scientific authoring tools: interactive data mining for constructive uses of citation networks. Information Processing \& Management. 46, 1–10 (2010).
@article{berendt2009authoring,
author = {Berendt, Bettina and Krause, Beate and Kolbe-Nusser, Sebastian},
journal = {Information Processing \& Management},
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%A Berendt, Bettina
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%A Kolbe-Nusser, Sebastian
%D 2010
%J Information Processing \& Management
%N 1
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%T Intelligent scientific authoring tools: interactive data mining for constructive uses of citation networks
%U https://lirias.kuleuven.be/handle/123456789/255612
%V 46 - 1.Hotho, A., Benz, D., Eisterlehner, F., Jäschke, R., Krause, B., Schmitz, C., Stumme, G.: {Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System für Wissenschaftler}. HMD -- Praxis der Wirtschaftsinformatik. Heft 271, 47–58 (2010).Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer größerer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenwärtigkeit, die ständige Verfügbarkeit, aber auch die Möglichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gründe für ihren gegenwärtigen Erfolg. Der Artikel führt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabläufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schließt mit Querbezügen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.
@article{HothoBenzEtAl10hmd,
abstract = {Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer größerer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenwärtigkeit, die ständige Verfügbarkeit, aber auch die Möglichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gründe für ihren gegenwärtigen Erfolg. Der Artikel führt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabläufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schließt mit Querbezügen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.},
author = {Hotho, Andreas and Benz, Dominik and Eisterlehner, Folke and Jäschke, Robert and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
journal = {HMD -- Praxis der Wirtschaftsinformatik},
keywords = {social-bookmarking},
month = {02},
pages = {47-58},
title = {{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System für Wissenschaftler}},
volume = {Heft 271},
year = 2010
}%0 Journal Article
%1 HothoBenzEtAl10hmd
%A Hotho, Andreas
%A Benz, Dominik
%A Eisterlehner, Folke
%A Jäschke, Robert
%A Krause, Beate
%A Schmitz, Christoph
%A Stumme, Gerd
%D 2010
%J HMD -- Praxis der Wirtschaftsinformatik
%P 47-58
%T {Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System für Wissenschaftler}
%V Heft 271
%X Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer größerer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenwärtigkeit, die ständige Verfügbarkeit, aber auch die Möglichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gründe für ihren gegenwärtigen Erfolg. Der Artikel führt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabläufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schließt mit Querbezügen zu aktuellen Forschungsfragen im Bereich Social Bookmarking. - 1.Hotho, A., Benz, D., Eisterlehner, F., J{ä}schke, R., Krause, B., Schmitz, C., Stumme, G.: {Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{ü}r Wissenschaftler}. HMD -- Praxis der Wirtschaftsinformatik. Heft 271, 47–58 (2010).Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer gr{ö}ßerer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenw{ä}rtigkeit, die st{ä}ndige Verf{ü}gbarkeit, aber auch die M{ö}glichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gr{ü}nde f{ü}r ihren gegenw{ä}rtigen Erfolg. Der Artikel f{ü}hrt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabl{ä}ufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schließt mit Querbez{ü}gen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.
@article{hotho2010publikationsmanagement,
abstract = {Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer gr{ö}ßerer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenw{ä}rtigkeit, die st{ä}ndige Verf{ü}gbarkeit, aber auch die M{ö}glichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gr{ü}nde f{ü}r ihren gegenw{ä}rtigen Erfolg. Der Artikel f{ü}hrt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabl{ä}ufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schließt mit Querbez{ü}gen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.},
author = {Hotho, Andreas and Benz, Dominik and Eisterlehner, Folke and J{ä}schke, Robert and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
journal = {HMD -- Praxis der Wirtschaftsinformatik},
keywords = {itegpub},
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title = {{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{ü}r Wissenschaftler}},
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}%0 Journal Article
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%A Hotho, Andreas
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%A Krause, Beate
%A Schmitz, Christoph
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%T {Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{ü}r Wissenschaftler}
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%X Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer gr{ö}ßerer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenw{ä}rtigkeit, die st{ä}ndige Verf{ü}gbarkeit, aber auch die M{ö}glichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gr{ü}nde f{ü}r ihren gegenw{ä}rtigen Erfolg. Der Artikel f{ü}hrt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabl{ä}ufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schließt mit Querbez{ü}gen zu aktuellen Forschungsfragen im Bereich Social Bookmarking. - 1.Körner, C., Benz, D., Strohmaier, M., Hotho, A., Stumme, G.: Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity. In: Proceedings of the 19th International World Wide Web Conference (WWW 2010). ACM, Raleigh, NC, USA (2010).Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise”, and (iii) in learning ontologies.
@inproceedings{koerner2010thinking,
abstract = {Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise”, and (iii) in learning ontologies.},
address = {Raleigh, NC, USA},
author = {Körner, Christian and Benz, Dominik and Strohmaier, Markus and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 19th International World Wide Web Conference (WWW 2010)},
keywords = {collaborative_verbosity},
month = {04},
publisher = {ACM},
title = {Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity},
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}%0 Conference Paper
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%A Benz, Dominik
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%A Hotho, Andreas
%A Stumme, Gerd
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%C Raleigh, NC, USA
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%I ACM
%T Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity
%U https://www.kde.cs.uni-kassel.de/benz/papers/2010/koerner2010thinking.pdf
%X Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise”, and (iii) in learning ontologies. - 1.Benz, D., Hotho, A., Jäschke, R., Krause, B., Stumme, G.: Query Logs as Folksonomies. Datenbank-Spektrum. 10, 15–24 (2010).Query logs provide a valuable resource for preference information in search. A user clicking on a specific resource after submitting a query indicates that the resource has some relevance with respect to the query. To leverage the information ofquery logs, one can relate submitted queries from specific users to their clicked resources and build a tripartite graph ofusers, resources and queries. This graph resembles the folksonomy structure of social bookmarking systems, where users addtags to resources. In this article, we summarize our work on building folksonomies from query log files. The focus is on threecomparative studies of the system’s content, structure and semantics. Our results show that query logs incorporate typicalfolksonomy properties and that approaches to leverage the inherent semantics of folksonomies can be applied to query logsas well.
@article{benz2010query,
abstract = {Query logs provide a valuable resource for preference information in search. A user clicking on a specific resource after submitting a query indicates that the resource has some relevance with respect to the query. To leverage the information ofquery logs, one can relate submitted queries from specific users to their clicked resources and build a tripartite graph ofusers, resources and queries. This graph resembles the folksonomy structure of social bookmarking systems, where users addtags to resources. In this article, we summarize our work on building folksonomies from query log files. The focus is on threecomparative studies of the system’s content, structure and semantics. Our results show that query logs incorporate typicalfolksonomy properties and that approaches to leverage the inherent semantics of folksonomies can be applied to query logsas well.},
author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd},
journal = {Datenbank-Spektrum},
keywords = {folsonomy},
month = {06},
number = 1,
pages = {15--24},
title = {Query Logs as Folksonomies},
volume = 10,
year = 2010
}%0 Journal Article
%1 benz2010query
%A Benz, Dominik
%A Hotho, Andreas
%A Jäschke, Robert
%A Krause, Beate
%A Stumme, Gerd
%D 2010
%J Datenbank-Spektrum
%N 1
%P 15--24
%T Query Logs as Folksonomies
%U http://dx.doi.org/10.1007/s13222-010-0004-8
%V 10
%X Query logs provide a valuable resource for preference information in search. A user clicking on a specific resource after submitting a query indicates that the resource has some relevance with respect to the query. To leverage the information ofquery logs, one can relate submitted queries from specific users to their clicked resources and build a tripartite graph ofusers, resources and queries. This graph resembles the folksonomy structure of social bookmarking systems, where users addtags to resources. In this article, we summarize our work on building folksonomies from query log files. The focus is on threecomparative studies of the system’s content, structure and semantics. Our results show that query logs incorporate typicalfolksonomy properties and that approaches to leverage the inherent semantics of folksonomies can be applied to query logsas well. - 1.Doerfel, S.: The Scaffolding of a Formal Context. In: Kryszkiewicz, M. and Obiedkov, S. (eds.) Concept Lattices and Their Applications 2010 - Proceedings of the 7th International Conference on Concept Lattices and Their Applications Sevilla, Spain, October 19-21, 2010. pp. 283–293. CEUR-WS (2010).The scaffolding of a complete lattice L of finite length was introduced by Rudolf Wille in 1976 as a relative subsemilattice of L that can be constructed using subdirect decomposition. The lattice is uniquely defined by its scaffolding and can be reconstructed from it. Using bonds, we demonstrate how the scaffolding can be constructed from a given formal context and thereby extend the notion of the scaffolding to doubly founded lattices. Further, we explain the creation of a suitable graphical representation of the scaffolding from the context.
@inproceedings{doerfel2010scaffolding,
abstract = {The scaffolding of a complete lattice L of finite length was introduced by Rudolf Wille in 1976 as a relative subsemilattice of L that can be constructed using subdirect decomposition. The lattice is uniquely defined by its scaffolding and can be reconstructed from it. Using bonds, we demonstrate how the scaffolding can be constructed from a given formal context and thereby extend the notion of the scaffolding to doubly founded lattices. Further, we explain the creation of a suitable graphical representation of the scaffolding from the context.},
author = {Doerfel, Stephan},
booktitle = {Concept Lattices and Their Applications 2010 - Proceedings of the 7th International Conference on Concept Lattices and Their Applications Sevilla, Spain, October 19-21, 2010.},
editor = {Kryszkiewicz, Marzena and Obiedkov, Sergei},
keywords = {itegpub},
month = 11,
pages = {283-293},
publisher = {CEUR-WS},
title = {The Scaffolding of a Formal Context},
volume = 672,
year = 2010
}%0 Conference Paper
%1 doerfel2010scaffolding
%A Doerfel, Stephan
%B Concept Lattices and Their Applications 2010 - Proceedings of the 7th International Conference on Concept Lattices and Their Applications Sevilla, Spain, October 19-21, 2010.
%D 2010
%E Kryszkiewicz, Marzena
%E Obiedkov, Sergei
%I CEUR-WS
%P 283-293
%T The Scaffolding of a Formal Context
%U http://ceur-ws.org/Vol-672/
%V 672
%X The scaffolding of a complete lattice L of finite length was introduced by Rudolf Wille in 1976 as a relative subsemilattice of L that can be constructed using subdirect decomposition. The lattice is uniquely defined by its scaffolding and can be reconstructed from it. Using bonds, we demonstrate how the scaffolding can be constructed from a given formal context and thereby extend the notion of the scaffolding to doubly founded lattices. Further, we explain the creation of a suitable graphical representation of the scaffolding from the context. - 1.Benz, D., Hotho, A., Stumme, G.: Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge. In: Proceedings of the 2nd Web Science Conference (WebSci10). , Raleigh, NC, USA (2010).
@inproceedings{benz2010semantics,
address = {Raleigh, NC, USA},
author = {Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 2nd Web Science Conference (WebSci10)},
keywords = {ontology},
title = {Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge},
year = 2010
}%0 Conference Paper
%1 benz2010semantics
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the 2nd Web Science Conference (WebSci10)
%C Raleigh, NC, USA
%D 2010
%T Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge - 1.Benz, D., Hotho, A., Jäschke, R., Stumme, G., Halle, A., Lima, A.G.S., Steenweg, H., Stefani, S.: Academic Publication Management with PUMA - collect, organize and share publications. In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., and Frommholz, I. (eds.) Proceedings of the European Conference on Research and Advanced Technology for Digital Libraries (ECDL) 2010. pp. 417–420. Springer, Berlin/Heidelberg (2010).The PUMA project fosters the Open Access movement und aims at a better support of the researcher’s publication work. PUMA stands for an integrated solution, where the upload of a publication results automatically in an update of both the personal and institutional homepage, the creation of an entry in a social bookmarking systems like BibSonomy, an entry in the academic reporting system of the university, and its publication in the institutional repository. In this poster, we present the main features of our solution.
@inproceedings{benz2010academic,
abstract = {The PUMA project fosters the Open Access movement und aims at a better support of the researcher’s publication work. PUMA stands for an integrated solution, where the upload of a publication results automatically in an update of both the personal and institutional homepage, the creation of an entry in a social bookmarking systems like BibSonomy, an entry in the academic reporting system of the university, and its publication in the institutional repository. In this poster, we present the main features of our solution.},
address = {Berlin/Heidelberg},
author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd and Halle, Axel and Lima, Angela Gerlach Sanches and Steenweg, Helge and Stefani, Sven},
booktitle = {Proceedings of the European Conference on Research and Advanced Technology for Digital Libraries (ECDL) 2010},
editor = {Lalmas, M. and Jose, J. and Rauber, A. and Sebastiani, F. and Frommholz, I.},
keywords = {itegpub},
pages = {417--420},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Academic Publication Management with PUMA - collect, organize and share publications},
volume = 6273,
year = 2010
}%0 Conference Paper
%1 benz2010academic
%A Benz, Dominik
%A Hotho, Andreas
%A Jäschke, Robert
%A Stumme, Gerd
%A Halle, Axel
%A Lima, Angela Gerlach Sanches
%A Steenweg, Helge
%A Stefani, Sven
%B Proceedings of the European Conference on Research and Advanced Technology for Digital Libraries (ECDL) 2010
%C Berlin/Heidelberg
%D 2010
%E Lalmas, M.
%E Jose, J.
%E Rauber, A.
%E Sebastiani, F.
%E Frommholz, I.
%I Springer
%P 417--420
%T Academic Publication Management with PUMA - collect, organize and share publications
%V 6273
%X The PUMA project fosters the Open Access movement und aims at a better support of the researcher’s publication work. PUMA stands for an integrated solution, where the upload of a publication results automatically in an update of both the personal and institutional homepage, the creation of an entry in a social bookmarking systems like BibSonomy, an entry in the academic reporting system of the university, and its publication in the institutional repository. In this poster, we present the main features of our solution. - 1.Benz, D., Hotho, A., Stützer, S., Stumme, G.: Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge. In: Proceedings of the 2nd Web Science Conference (WebSci10). , Raleigh, NC, USA (2010).
@inproceedings{benz2010semantics,
address = {Raleigh, NC, USA},
author = {Benz, Dominik and Hotho, Andreas and Stützer, Stefan and Stumme, Gerd},
booktitle = {Proceedings of the 2nd Web Science Conference (WebSci10)},
keywords = {itegpub},
title = {Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge},
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}%0 Conference Paper
%1 benz2010semantics
%A Benz, Dominik
%A Hotho, Andreas
%A Stützer, Stefan
%A Stumme, Gerd
%B Proceedings of the 2nd Web Science Conference (WebSci10)
%C Raleigh, NC, USA
%D 2010
%T Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge
%U https://www.kde.cs.uni-kassel.de/pub/pdf/benz2010semantics.pdf - 1.Krause, B., Lerch, H., Hotho, A., Roßnagel, A., Stumme, G.: Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy. Informatik-Spektrum. 1–12 (2010). https://doi.org/10.1007/s00287-010-0485-8.Soziale Tagging-Systeme gehören zu den in den vergangenen Jahren entstandenen Web2.0-Systemen. Sie ermöglichen es Anwendern, beliebige Informationen in das Internet einzustellen und untereinander auszutauschen. Je nach Anbieter verlinken Nutzer Videos, Fotos oder Webseiten und beschreiben die eingestellten Medien mit entsprechenden Schlagwörtern (Tags). Die damit einhergehende freiwillige Preisgabe oftmals persönlicher Informationen wirft Fragen im Bereich der informationellen Selbstbestimmung auf. Dieses Grundrecht gewährleistet dem Einzelnen, grundsätzlich selbst über die Preisgabe und Verwendung seiner persönlichen Daten zu bestimmen. Für viele Funktionalitäten, wie beispielsweise Empfehlungsdienste oder die Bereitstellung einer API, ist eine solche Kontrolle allerdings schwierig zu gestalten. Oftmals existieren keine Richtlinien, inwieweit Dienstanbieter und weitere Dritte diese öffentlichen Daten (und weitere Daten, die bei der Nutzung des Systems anfallen) nutzen dürfen. Dieser Artikel diskutiert anhand eines konkreten Systems typische, für den Datenschutz relevante Funktionalitäten und gibt Handlungsanweisungen für eine datenschutzkonforme technische Gestaltung.
@article{springerlink:10.1007/s00287-010-0485-8,
abstract = {Soziale Tagging-Systeme gehören zu den in den vergangenen Jahren entstandenen Web2.0-Systemen. Sie ermöglichen es Anwendern, beliebige Informationen in das Internet einzustellen und untereinander auszutauschen. Je nach Anbieter verlinken Nutzer Videos, Fotos oder Webseiten und beschreiben die eingestellten Medien mit entsprechenden Schlagwörtern (Tags). Die damit einhergehende freiwillige Preisgabe oftmals persönlicher Informationen wirft Fragen im Bereich der informationellen Selbstbestimmung auf. Dieses Grundrecht gewährleistet dem Einzelnen, grundsätzlich selbst über die Preisgabe und Verwendung seiner persönlichen Daten zu bestimmen. Für viele Funktionalitäten, wie beispielsweise Empfehlungsdienste oder die Bereitstellung einer API, ist eine solche Kontrolle allerdings schwierig zu gestalten. Oftmals existieren keine Richtlinien, inwieweit Dienstanbieter und weitere Dritte diese öffentlichen Daten (und weitere Daten, die bei der Nutzung des Systems anfallen) nutzen dürfen. Dieser Artikel diskutiert anhand eines konkreten Systems typische, für den Datenschutz relevante Funktionalitäten und gibt Handlungsanweisungen für eine datenschutzkonforme technische Gestaltung.},
address = {Berlin / Heidelberg},
author = {Krause, Beate and Lerch, Hana and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd},
journal = {Informatik-Spektrum},
keywords = {itegpub},
pages = {1-12},
publisher = {Springer},
title = {Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy},
year = 2010
}%0 Journal Article
%1 springerlink:10.1007/s00287-010-0485-8
%A Krause, Beate
%A Lerch, Hana
%A Hotho, Andreas
%A Roßnagel, Alexander
%A Stumme, Gerd
%C Berlin / Heidelberg
%D 2010
%I Springer
%J Informatik-Spektrum
%P 1-12
%R 10.1007/s00287-010-0485-8
%T Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy
%U http://dx.doi.org/10.1007/s00287-010-0485-8
%X Soziale Tagging-Systeme gehören zu den in den vergangenen Jahren entstandenen Web2.0-Systemen. Sie ermöglichen es Anwendern, beliebige Informationen in das Internet einzustellen und untereinander auszutauschen. Je nach Anbieter verlinken Nutzer Videos, Fotos oder Webseiten und beschreiben die eingestellten Medien mit entsprechenden Schlagwörtern (Tags). Die damit einhergehende freiwillige Preisgabe oftmals persönlicher Informationen wirft Fragen im Bereich der informationellen Selbstbestimmung auf. Dieses Grundrecht gewährleistet dem Einzelnen, grundsätzlich selbst über die Preisgabe und Verwendung seiner persönlichen Daten zu bestimmen. Für viele Funktionalitäten, wie beispielsweise Empfehlungsdienste oder die Bereitstellung einer API, ist eine solche Kontrolle allerdings schwierig zu gestalten. Oftmals existieren keine Richtlinien, inwieweit Dienstanbieter und weitere Dritte diese öffentlichen Daten (und weitere Daten, die bei der Nutzung des Systems anfallen) nutzen dürfen. Dieser Artikel diskutiert anhand eines konkreten Systems typische, für den Datenschutz relevante Funktionalitäten und gibt Handlungsanweisungen für eine datenschutzkonforme technische Gestaltung. - 1.Kluegl, P., Hotho, A., Puppe, F.: Local Adaptive Extraction of References. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., and Schultz, T. (eds.) KI 2010: Advances in Artificial Intelligence, 33rd Annual German Conference on AI. pp. 40–47. Springer (2010).The accurate extraction of scholarly reference information from scientific publications is essential for many useful applications like BibTeX management systems or citation analysis. Automatic extraction methods suffer from the heterogeneity of reference notation, no matter wether the extraction model was handcrafted or learnt from labeled data. However, references of the same paper or journal are usually homogeneous. We exploit this local consistency with a novel approach. Given some initial information from such a reference section, we try to derived generalized patterns. These patterns are used to create a local model of the current document. The local model helps to identify errors and to improve the extracted information incrementally during the extraction process. Our approach is implemented with handcrafted transformation rules working on a meta-level being able to correct the information independent of the applied layout style. The experimental results compete very well with the state of the art methods and show an extremely high performance on consistent reference sections.
@inproceedings{2010-KI-KHP,
abstract = {The accurate extraction of scholarly reference information from scientific publications is essential for many useful applications like BibTeX management systems or citation analysis. Automatic extraction methods suffer from the heterogeneity of reference notation, no matter wether the extraction model was handcrafted or learnt from labeled data. However, references of the same paper or journal are usually homogeneous. We exploit this local consistency with a novel approach. Given some initial information from such a reference section, we try to derived generalized patterns. These patterns are used to create a local model of the current document. The local model helps to identify errors and to improve the extracted information incrementally during the extraction process. Our approach is implemented with handcrafted transformation rules working on a meta-level being able to correct the information independent of the applied layout style. The experimental results compete very well with the state of the art methods and show an extremely high performance on consistent reference sections.},
author = {Kluegl, Peter and Hotho, Andreas and Puppe, Frank},
booktitle = {KI 2010: Advances in Artificial Intelligence, 33rd Annual German Conference on AI},
editor = {Dillmann, Rüdiger and Beyerer, Jürgen and Hanebeck, Uwe D. and Schultz, Tanja},
keywords = {ie},
pages = {40-47},
publisher = {Springer},
series = {LNAI 6359},
title = {Local Adaptive Extraction of References},
year = 2010
}%0 Conference Paper
%1 2010-KI-KHP
%A Kluegl, Peter
%A Hotho, Andreas
%A Puppe, Frank
%B KI 2010: Advances in Artificial Intelligence, 33rd Annual German Conference on AI
%D 2010
%E Dillmann, Rüdiger
%E Beyerer, Jürgen
%E Hanebeck, Uwe D.
%E Schultz, Tanja
%I Springer
%P 40-47
%T Local Adaptive Extraction of References
%U http://ki.informatik.uni-wuerzburg.de/papers/pkluegl/2010-KI-LAER.pdf
%X The accurate extraction of scholarly reference information from scientific publications is essential for many useful applications like BibTeX management systems or citation analysis. Automatic extraction methods suffer from the heterogeneity of reference notation, no matter wether the extraction model was handcrafted or learnt from labeled data. However, references of the same paper or journal are usually homogeneous. We exploit this local consistency with a novel approach. Given some initial information from such a reference section, we try to derived generalized patterns. These patterns are used to create a local model of the current document. The local model helps to identify errors and to improve the extracted information incrementally during the extraction process. Our approach is implemented with handcrafted transformation rules working on a meta-level being able to correct the information independent of the applied layout style. The experimental results compete very well with the state of the art methods and show an extremely high performance on consistent reference sections.
%@ 978-3-642-16110-0 - 1.Berendt, B., Hotho, A., Stumme, G.: Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0. Web Semantics: Science, Services and Agents on the World Wide Web. 8, 95–96 (2010). https://doi.org/DOI: 10.1016/j.websem.2010.04.008.
@article{berendt2010bridging,
author = {Berendt, Bettina and Hotho, Andreas and Stumme, Gerd},
journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
keywords = {itegpub},
note = {Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences},
number = {2-3},
pages = {95 - 96},
title = {Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0},
volume = 8,
year = 2010
}%0 Journal Article
%1 berendt2010bridging
%A Berendt, Bettina
%A Hotho, Andreas
%A Stumme, Gerd
%D 2010
%J Web Semantics: Science, Services and Agents on the World Wide Web
%N 2-3
%P 95 - 96
%R DOI: 10.1016/j.websem.2010.04.008
%T Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0
%U http://www.sciencedirect.com/science/article/B758F-4YXK4HW-1/2/4cb514565477c54160b5e6eb716c32d7
%V 8 - 1.Lemmerich, F., Rohlfs, M., Atzmueller, M.: Fast Discovery of Relevant Subgroup Patterns. In: Proc. 23rd FLAIRS Conference (2010).
@inproceedings{LA:10,
author = {Lemmerich, Florian and Rohlfs, Matthias and Atzmueller, Martin},
booktitle = {Proc. 23rd FLAIRS Conference},
keywords = {local},
title = {Fast Discovery of Relevant Subgroup Patterns},
year = 2010
}%0 Conference Paper
%1 LA:10
%A Lemmerich, Florian
%A Rohlfs, Matthias
%A Atzmueller, Martin
%B Proc. 23rd FLAIRS Conference
%D 2010
%T Fast Discovery of Relevant Subgroup Patterns - 1.Atzmueller, M., Beer, S.: Validation of Mixed-Structured Data Using Pattern Mining and Information Extraction. In: Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS). University of Ilmenau (2010).
@inproceedings{AB:10,
author = {Atzmueller, Martin and Beer, Stephanie},
booktitle = {Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS)},
keywords = {itegpub},
publisher = {University of Ilmenau},
title = {Validation of Mixed-Structured Data Using Pattern Mining and Information Extraction},
year = 2010
}%0 Conference Paper
%1 AB:10
%A Atzmueller, Martin
%A Beer, Stephanie
%B Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS)
%D 2010
%I University of Ilmenau
%T Validation of Mixed-Structured Data Using Pattern Mining and Information Extraction - 1.Weiss, C., Atzmueller, M.: EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data. Quality and Reliability Engineering. (2010).
@article{WA:10,
author = {Weiss, Christian and Atzmueller, Martin},
journal = {Quality and Reliability Engineering},
keywords = {itegpub},
title = {EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data},
year = 2010
}%0 Journal Article
%1 WA:10
%A Weiss, Christian
%A Atzmueller, Martin
%D 2010
%J Quality and Reliability Engineering
%T EWMA Control Charts for Monitoring Binary Processes with Applications to Medical Diagnosis Data - 1.Hotho, A., {Ulslev Pedersen}, R., Wurst, M.: Ubiquitous Data. Lecture Notes in Computer Science. 61–74 (2010).
@article{hotho2010ubiquitous,
author = {Hotho, Andreas and {Ulslev Pedersen}, Rasmus and Wurst, Michael},
journal = {Lecture Notes in Computer Science},
keywords = 2010,
number = 6202,
pages = {61--74},
publisher = {Springer},
title = {Ubiquitous Data},
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}%0 Journal Article
%1 hotho2010ubiquitous
%A Hotho, Andreas
%A {Ulslev Pedersen}, Rasmus
%A Wurst, Michael
%D 2010
%I Springer
%J Lecture Notes in Computer Science
%N 6202
%P 61--74
%T Ubiquitous Data
%U http://rd.springer.com/content/pdf/10.1007%2F978-3-642-16392-0_4.pdf - 1.Atzmueller, M., Mitzlaff, F.: {Towards Mining Descriptive Community Patterns}. In: Workshop on Mining Patterns and Subgroups. Lorentz Center, Leiden, The Netherlands. Awarded with the Best Discovery Award (2010).
@inproceedings{atzmueller2010towards,
author = {Atzmueller, Martin and Mitzlaff, Folke},
booktitle = {Workshop on Mining Patterns and Subgroups},
keywords = {itegpub},
publisher = {Lorentz Center, Leiden, The Netherlands. Awarded with the Best Discovery Award},
title = {{Towards Mining Descriptive Community Patterns}},
year = 2010
}%0 Conference Paper
%1 atzmueller2010towards
%A Atzmueller, Martin
%A Mitzlaff, Folke
%B Workshop on Mining Patterns and Subgroups
%D 2010
%I Lorentz Center, Leiden, The Netherlands. Awarded with the Best Discovery Award
%T {Towards Mining Descriptive Community Patterns} - 1.Toepfer, M., Kluegl, P., Hotho, A., Puppe., F.: Conditional Random Fields For Local Adaptive Reference Extraction. In: Atzmüller, M., Benz, D., Hotho, A., and Stumme, G. (eds.) Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen {\&} Adaptivitaet. , Kassel, Germany (2010).The accurate extraction of bibliographic information from scientific publications is an active field of research. Machine learning and sequence labeling approaches like Conditional Random Fields (CRF) are often applied for this reference extraction task, but still suffer from the ambiguity of reference notation. Reference sections apply a predefined style guide and contain only homogeneous references. Therefore, other references of the same paper or journal often provide evidence how the fields of a reference are correctly labeled. We propose a novel approach that exploits the similarities within a document. Our process model uses information of unlabeled documents directly during the extraction task in order to automatically adapt to the perceived style guide. This is implemented by changing the manifestation of the features for the applied CRF. The experimental results show considerable improvements compared to the common approach. We achieve an average F1 score of 96.7% and an instance accuracy of 85.4% on the test data set.
@inproceedings{kdml21,
abstract = {The accurate extraction of bibliographic information from scientific publications is an active field of research. Machine learning and sequence labeling approaches like Conditional Random Fields (CRF) are often applied for this reference extraction task, but still suffer from the ambiguity of reference notation. Reference sections apply a predefined style guide and contain only homogeneous references. Therefore, other references of the same paper or journal often provide evidence how the fields of a reference are correctly labeled. We propose a novel approach that exploits the similarities within a document. Our process model uses information of unlabeled documents directly during the extraction task in order to automatically adapt to the perceived style guide. This is implemented by changing the manifestation of the features for the applied CRF. The experimental results show considerable improvements compared to the common approach. We achieve an average F1 score of 96.7% and an instance accuracy of 85.4% on the test data set.},
address = {Kassel, Germany},
author = {Toepfer, Martin and Kluegl, Peter and Hotho, Andreas and Puppe., Frank},
booktitle = {Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen {\&} Adaptivitaet},
crossref = {lwa2010},
editor = {Atzmüller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
keywords = {extraction},
title = {Conditional Random Fields For Local Adaptive Reference Extraction},
year = 2010
}%0 Conference Paper
%1 kdml21
%A Toepfer, Martin
%A Kluegl, Peter
%A Hotho, Andreas
%A Puppe., Frank
%B Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen {\&} Adaptivitaet
%C Kassel, Germany
%D 2010
%E Atzmüller, Martin
%E Benz, Dominik
%E Hotho, Andreas
%E Stumme, Gerd
%T Conditional Random Fields For Local Adaptive Reference Extraction
%U https://www.kde.cs.uni-kassel.de/conf/lwa10/papers/kdml21.pdf
%X The accurate extraction of bibliographic information from scientific publications is an active field of research. Machine learning and sequence labeling approaches like Conditional Random Fields (CRF) are often applied for this reference extraction task, but still suffer from the ambiguity of reference notation. Reference sections apply a predefined style guide and contain only homogeneous references. Therefore, other references of the same paper or journal often provide evidence how the fields of a reference are correctly labeled. We propose a novel approach that exploits the similarities within a document. Our process model uses information of unlabeled documents directly during the extraction task in order to automatically adapt to the perceived style guide. This is implemented by changing the manifestation of the features for the applied CRF. The experimental results show considerable improvements compared to the common approach. We achieve an average F1 score of 96.7% and an instance accuracy of 85.4% on the test data set. - 1.Kaempgen, B., Lemmerich, F., Atzmueller, M.: Decision-Maker-Aware Design of Descriptive Data Mining. In: Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS) (2010).
@inproceedings{KLA:10,
author = {Kaempgen, Benedikt and Lemmerich, Florian and Atzmueller, Martin},
booktitle = {Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS)},
keywords = {itegpub},
title = {Decision-Maker-Aware Design of Descriptive Data Mining},
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}%0 Conference Paper
%1 KLA:10
%A Kaempgen, Benedikt
%A Lemmerich, Florian
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%B Proc. 55th IWK, International Workshop on Design, Evaluation and Refinement of Intelligent Systems (DERIS)
%D 2010
%T Decision-Maker-Aware Design of Descriptive Data Mining - 1.Atzmueller, M., Roth-Berghofer, T.: Towards Explanation-Aware Social Software: Applying the Mining and Analysis Continuum of Explaining. In: Proc. Workshop on Explanation-aware Computing ExaCt 2010 @ ECAI 2010 (2010).
@inproceedings{AR:10b,
author = {Atzmueller, Martin and Roth-Berghofer, Thomas},
booktitle = {Proc. Workshop on Explanation-aware Computing ExaCt 2010 @ ECAI 2010},
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title = {Towards Explanation-Aware Social Software: Applying the Mining and Analysis Continuum of Explaining},
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}%0 Conference Paper
%1 AR:10b
%A Atzmueller, Martin
%A Roth-Berghofer, Thomas
%B Proc. Workshop on Explanation-aware Computing ExaCt 2010 @ ECAI 2010
%D 2010
%T Towards Explanation-Aware Social Software: Applying the Mining and Analysis Continuum of Explaining - 1.Atzmueller, M., Roth-Berghofer, T.: Ready for the MACE? The Mining and Analysis Continuum of Explaining Uncovered. Deutsches Forschungszentrum für Künstliche Intelligenz (2010).
@techreport{AR:10c,
author = {Atzmueller, Martin and Roth-Berghofer, Thomas},
institution = {Deutsches Forschungszentrum für Künstliche Intelligenz},
keywords = {itegpub},
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title = {Ready for the MACE? The Mining and Analysis Continuum of Explaining Uncovered},
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%T Ready for the MACE? The Mining and Analysis Continuum of Explaining Uncovered - 1.Hotho, A.: Data Mining on Folksonomies. In: Armano, G., de Gemmis, M., Semeraro, G., and Vargiu, E. (eds.) Intelligent Information Access. pp. 57–82. Springer, Berlin / Heidelberg (2010). https://doi.org/10.1007/978-3-642-14000-6_4.Social resource sharing systems are central elements of the Web 2.0 and use all the same kind of lightweight knowledge representation, called folksonomy. As these systems are easy to use, they attract huge masses of users. Data Mining provides methods to analyze data and to learn models which can be used to support users. The application and adaptation of known data mining algorithms to folksonomies with the goal to support the users of such systems and to extract valuable information with a special focus on the Semantic Web is the main target of this paper. In this work we give a short introduction into folksonomies with a focus on our own system BibSonomy. Based on the analysis we made on a large folksonomy dataset, we present the application of data mining algorithms on three different tasks, namely spam detection, ranking and recommendation. To bridge the gap between folksonomies and the Semantic Web, we apply association rule mining to extract relations and present a deeper analysis of statistical measures which can be used to extract tag relations. This approach is complemented by presenting two approaches to extract conceptualizations from folksonomies.
@incollection{springerlink:10.1007/978-3-642-14000-6_4,
abstract = {Social resource sharing systems are central elements of the Web 2.0 and use all the same kind of lightweight knowledge representation, called folksonomy. As these systems are easy to use, they attract huge masses of users. Data Mining provides methods to analyze data and to learn models which can be used to support users. The application and adaptation of known data mining algorithms to folksonomies with the goal to support the users of such systems and to extract valuable information with a special focus on the Semantic Web is the main target of this paper. In this work we give a short introduction into folksonomies with a focus on our own system BibSonomy. Based on the analysis we made on a large folksonomy dataset, we present the application of data mining algorithms on three different tasks, namely spam detection, ranking and recommendation. To bridge the gap between folksonomies and the Semantic Web, we apply association rule mining to extract relations and present a deeper analysis of statistical measures which can be used to extract tag relations. This approach is complemented by presenting two approaches to extract conceptualizations from folksonomies.},
address = {Berlin / Heidelberg},
author = {Hotho, Andreas},
booktitle = {Intelligent Information Access},
editor = {Armano, Giuliano and de Gemmis, Marco and Semeraro, Giovanni and Vargiu, Eloisa},
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pages = {57-82},
publisher = {Springer},
series = {Studies in Computational Intelligence},
title = {Data Mining on Folksonomies},
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}%0 Book Section
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%V 301
%X Social resource sharing systems are central elements of the Web 2.0 and use all the same kind of lightweight knowledge representation, called folksonomy. As these systems are easy to use, they attract huge masses of users. Data Mining provides methods to analyze data and to learn models which can be used to support users. The application and adaptation of known data mining algorithms to folksonomies with the goal to support the users of such systems and to extract valuable information with a special focus on the Semantic Web is the main target of this paper. In this work we give a short introduction into folksonomies with a focus on our own system BibSonomy. Based on the analysis we made on a large folksonomy dataset, we present the application of data mining algorithms on three different tasks, namely spam detection, ranking and recommendation. To bridge the gap between folksonomies and the Semantic Web, we apply association rule mining to extract relations and present a deeper analysis of statistical measures which can be used to extract tag relations. This approach is complemented by presenting two approaches to extract conceptualizations from folksonomies. - 1.Lerch, H., Krause, B., Hotho, A., Roßnagel, A., Stumme, G.: Social Bookmarking-Systeme – die unerkannten Datensammler - Ungewollte personenbezogene Datenverabeitung?. MultiMedia und Recht. 7, 454–458 (2010).
@article{lerch2010datenschutz,
author = {Lerch, Hana and Krause, Beate and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd},
journal = {MultiMedia und Recht},
keywords = {social-bookmarking},
pages = {454-458},
title = {Social Bookmarking-Systeme – die unerkannten Datensammler - Ungewollte personenbezogene Datenverabeitung?},
volume = 7,
year = 2010
}%0 Journal Article
%1 lerch2010datenschutz
%A Lerch, Hana
%A Krause, Beate
%A Hotho, Andreas
%A Roßnagel, Alexander
%A Stumme, Gerd
%D 2010
%J MultiMedia und Recht
%P 454-458
%T Social Bookmarking-Systeme – die unerkannten Datensammler - Ungewollte personenbezogene Datenverabeitung?
%V 7 - 1.Mitzlaff, F., Atzmueller, M., Benz, D., Hotho, A., Stumme, G.: Community Assessment using Evidence Networks. In: Proceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010). , Barcelona, Spain (2010).Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well.
@inproceedings{mitzlaff2010community,
abstract = {Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well.},
address = {Barcelona, Spain},
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}%0 Conference Paper
%1 mitzlaff2010community
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%A Atzmueller, Martin
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010)
%C Barcelona, Spain
%D 2010
%T Community Assessment using Evidence Networks
%U https://www.kde.cs.uni-kassel.de/atzmueller/paper/mitzlaff-community-assessment-muse-2010.pdf
%X Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well.
2009
- 1.Markines, B., Cattuto, C., Menczer, F., Benz, D., Hotho, A., Stumme, G.: Evaluating Similarity Measures for Emergent Semantics of Social Tagging. In: 18th International World Wide Web Conference. pp. 641–641 (2009).Social bookmarking systems and their emergent information structures, known as folksonomies, are increasingly important data sources for Semantic Web applications. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as navigation support, semantic search, and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures derived from established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity among tags and resources, considering different ways to aggregate annotations across users. After comparing how tag similarity measures predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory. We also investigate the issue of scalability. We ?nd that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity.
@inproceedings{www200965,
abstract = {Social bookmarking systems and their emergent information structures, known as folksonomies, are increasingly important data sources for Semantic Web applications. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as navigation support, semantic search, and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures derived from established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity among tags and resources, considering different ways to aggregate annotations across users. After comparing how tag similarity measures predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory. We also investigate the issue of scalability. We ?nd that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity.},
author = {Markines, Benjamin and Cattuto, Ciro and Menczer, Filippo and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {18th International World Wide Web Conference},
keywords = {social_similarity},
month = {04},
pages = {641--641},
title = {Evaluating Similarity Measures for Emergent Semantics of Social Tagging},
year = 2009
}%0 Conference Paper
%1 www200965
%A Markines, Benjamin
%A Cattuto, Ciro
%A Menczer, Filippo
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B 18th International World Wide Web Conference
%D 2009
%P 641--641
%T Evaluating Similarity Measures for Emergent Semantics of Social Tagging
%U http://www2009.eprints.org/65/
%X Social bookmarking systems and their emergent information structures, known as folksonomies, are increasingly important data sources for Semantic Web applications. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as navigation support, semantic search, and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures derived from established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity among tags and resources, considering different ways to aggregate annotations across users. After comparing how tag similarity measures predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory. We also investigate the issue of scalability. We ?nd that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity. - 1.Voss, J., Hotho, A., Jäschke, R.: Mapping Bibliographic Records with Bibliographic Hash Keys. In: Kuhlen, R. (ed.) Information: Droge, Ware oder Commons?. Verlag Werner Hülsbusch (2009).This poster presents a set of hash keys for bibliographic records called bibkeys. Unlike other methods of duplicate detection, bibkeys can directly be calculated from a set of basic metadata fields (title, authors/editors, year). It is shown how bibkeys are used to map similar bibliographic records in BibSonomy and among distributed library catalogs and other distributed databases.
@inproceedings{voss2009mapping,
abstract = {This poster presents a set of hash keys for bibliographic records called bibkeys. Unlike other methods of duplicate detection, bibkeys can directly be calculated from a set of basic metadata fields (title, authors/editors, year). It is shown how bibkeys are used to map similar bibliographic records in BibSonomy and among distributed library catalogs and other distributed databases.},
author = {Voss, Jakob and Hotho, Andreas and Jäschke, Robert},
booktitle = {Information: Droge, Ware oder Commons?},
editor = {Kuhlen, Rainer},
keywords = {key},
organization = {Hochschulverband Informationswissenschaft},
publisher = {Verlag Werner Hülsbusch},
series = {Proceedings of the ISI},
title = {Mapping Bibliographic Records with Bibliographic Hash Keys},
year = 2009
}%0 Conference Paper
%1 voss2009mapping
%A Voss, Jakob
%A Hotho, Andreas
%A Jäschke, Robert
%B Information: Droge, Ware oder Commons?
%D 2009
%E Kuhlen, Rainer
%I Verlag Werner Hülsbusch
%T Mapping Bibliographic Records with Bibliographic Hash Keys
%U http://hdl.handle.net/10760/12697
%X This poster presents a set of hash keys for bibliographic records called bibkeys. Unlike other methods of duplicate detection, bibkeys can directly be calculated from a set of basic metadata fields (title, authors/editors, year). It is shown how bibkeys are used to map similar bibliographic records in BibSonomy and among distributed library catalogs and other distributed databases. - 1.Scholz, C.: Die Schwierigkeit des k-Median Clusterings für Bregman-Divergenzen, (2009).
@mastersthesis{scholz2009schwierigkeit,
author = {Scholz, Christoph},
keywords = {k-median},
school = {University of Paderborn},
title = {Die Schwierigkeit des k-Median Clusterings für Bregman-Divergenzen},
year = 2009
}%0 Thesis
%1 scholz2009schwierigkeit
%A Scholz, Christoph
%D 2009
%T Die Schwierigkeit des k-Median Clusterings für Bregman-Divergenzen - 1.Hotho, A., Jäschke, R., Benz, D., Grahl, M., Krause, B., Schmitz, C., Stumme, G.: Social Bookmarking am Beispiel BibSonomy. In: Blumauer, A. and Pellegrini, T. (eds.) Social Semantic Web. pp. 363–391. Springer, Berlin, Heidelberg (2009). https://doi.org/10.1007/978-3-540-72216-8.BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitung der Universität Kassel. Es erlaubt das Speichern und Organisieren von Web-Lesezeichen und Metadaten für wissenschaftlichePublikationen. In diesem Beitrag beschreiben wir die von BibSonomy bereitgestellte Funktionalität, die dahinter stehende Architektursowie das zugrunde liegende Datenmodell. Ferner erläutern wir Anwendungsbeispiele und gehen auf Methoden zur Analyse der in BibSonomy und ähnlichen Systemen enthaltenen Daten ein.
@incollection{hotho2008social,
abstract = {BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitung der Universität Kassel. Es erlaubt das Speichern und Organisieren von Web-Lesezeichen und Metadaten für wissenschaftlichePublikationen. In diesem Beitrag beschreiben wir die von BibSonomy bereitgestellte Funktionalität, die dahinter stehende Architektursowie das zugrunde liegende Datenmodell. Ferner erläutern wir Anwendungsbeispiele und gehen auf Methoden zur Analyse der in BibSonomy und ähnlichen Systemen enthaltenen Daten ein.},
address = {Berlin, Heidelberg},
author = {Hotho, Andreas and Jäschke, Robert and Benz, Dominik and Grahl, Miranda and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
booktitle = {Social Semantic Web},
chapter = 18,
editor = {Blumauer, Andreas and Pellegrini, Tassilo},
keywords = {bookmarking},
pages = {363--391},
publisher = {Springer},
series = {X.media.press},
title = {Social Bookmarking am Beispiel BibSonomy},
year = 2009
}%0 Book Section
%1 hotho2008social
%A Hotho, Andreas
%A Jäschke, Robert
%A Benz, Dominik
%A Grahl, Miranda
%A Krause, Beate
%A Schmitz, Christoph
%A Stumme, Gerd
%B Social Semantic Web
%C Berlin, Heidelberg
%D 2009
%E Blumauer, Andreas
%E Pellegrini, Tassilo
%I Springer
%P 363--391
%R 10.1007/978-3-540-72216-8
%T Social Bookmarking am Beispiel BibSonomy
%U http://dx.doi.org/10.1007/978-3-540-72216-8_18
%X BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitung der Universität Kassel. Es erlaubt das Speichern und Organisieren von Web-Lesezeichen und Metadaten für wissenschaftlichePublikationen. In diesem Beitrag beschreiben wir die von BibSonomy bereitgestellte Funktionalität, die dahinter stehende Architektursowie das zugrunde liegende Datenmodell. Ferner erläutern wir Anwendungsbeispiele und gehen auf Methoden zur Analyse der in BibSonomy und ähnlichen Systemen enthaltenen Daten ein.
%& 18
%@ 978-3-540-72215-1 - 1.Atzmueller, M., Lemmerich, F., Krause, B., Hotho, A.: {Towards Understanding Spammers - Discovering Local Patterns for Concept Characterization and Description}. In: Knobbe, J.F.A. (ed.) Proc. LeGo-09: From Local Patterns to Global Models, Workshop at the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (2009).
@inproceedings{ALKH:09,
author = {Atzmueller, Martin and Lemmerich, Florian and Krause, Beate and Hotho, Andreas},
booktitle = {Proc. LeGo-09: From Local Patterns to Global Models, Workshop at the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
editor = {Knobbe, Johannes Fürnkranz Arno},
keywords = {bibsonomy},
note = {accepted},
title = {{Towards Understanding Spammers - Discovering Local Patterns for Concept Characterization and Description}},
year = 2009
}%0 Conference Paper
%1 ALKH:09
%A Atzmueller, Martin
%A Lemmerich, Florian
%A Krause, Beate
%A Hotho, Andreas
%B Proc. LeGo-09: From Local Patterns to Global Models, Workshop at the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
%D 2009
%E Knobbe, Johannes Fürnkranz Arno
%T {Towards Understanding Spammers - Discovering Local Patterns for Concept Characterization and Description}
%U http://www.ke.tu-darmstadt.de/events/LeGo-09/04-Atzmueller.pdf - 1.Doerfel, S.: Gerüste Formaler Kontexte, (2009).1976 wurde von Rudolf Wille das Gerüst eines vollständigen Verbandes V endlicher Länge eingeführt. Dieses besteht aus einer (geordneten) Teilmenge von V, aus der der gesamte Verband rekonstruiert werden kann. In der Formalen Begriffsanalyse werden vollständige Verbände durch Kontexte beschrieben. Um mit diesen arbeiten zu können, wurden diverse verbandstheoretische Konzepte und Resultate für vollständige Verbände adaptiert und begriffsanalytisch, d. h. mit Hilfe von Kontexten formuliert. Ein Ziel dieser Diplomarbeit ist es, die Konstruktion des Gerüstes eines Begriffsverbandes aus einem Kontext heraus beschreiben zu können. Die Anwendbarkeit des Gerüstes wird dabei von vollständigen Verbänden endlicher Länge auf doppelt fundierte vollständige Verbände (bzw. deren reduzierte Kontexte) erweitert. Im zweiten Teil der Arbeit wird die von M_3 erzeugte Varietät betrachtet. Die darin enthaltenen doppelt fundierten vollständigen Verbände werden anhand ihrer reduzierten Kontexte charakterisiert.
@mastersthesis{doerfel2009gerste,
abstract = {1976 wurde von Rudolf Wille das Gerüst eines vollständigen Verbandes V endlicher Länge eingeführt. Dieses besteht aus einer (geordneten) Teilmenge von V, aus der der gesamte Verband rekonstruiert werden kann. In der Formalen Begriffsanalyse werden vollständige Verbände durch Kontexte beschrieben. Um mit diesen arbeiten zu können, wurden diverse verbandstheoretische Konzepte und Resultate für vollständige Verbände adaptiert und begriffsanalytisch, d. h. mit Hilfe von Kontexten formuliert. Ein Ziel dieser Diplomarbeit ist es, die Konstruktion des Gerüstes eines Begriffsverbandes aus einem Kontext heraus beschreiben zu können. Die Anwendbarkeit des Gerüstes wird dabei von vollständigen Verbänden endlicher Länge auf doppelt fundierte vollständige Verbände (bzw. deren reduzierte Kontexte) erweitert. Im zweiten Teil der Arbeit wird die von M_3 erzeugte Varietät betrachtet. Die darin enthaltenen doppelt fundierten vollständigen Verbände werden anhand ihrer reduzierten Kontexte charakterisiert.},
author = {Doerfel, Stephan},
howpublished = {Diplomarbeit},
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keywords = {diplomarbeit},
school = {TU Dresden},
title = {Gerüste Formaler Kontexte},
type = {Diplomarbeit},
year = 2009
}%0 Thesis
%1 doerfel2009gerste
%A Doerfel, Stephan
%D 2009
%T Gerüste Formaler Kontexte
%X 1976 wurde von Rudolf Wille das Gerüst eines vollständigen Verbandes V endlicher Länge eingeführt. Dieses besteht aus einer (geordneten) Teilmenge von V, aus der der gesamte Verband rekonstruiert werden kann. In der Formalen Begriffsanalyse werden vollständige Verbände durch Kontexte beschrieben. Um mit diesen arbeiten zu können, wurden diverse verbandstheoretische Konzepte und Resultate für vollständige Verbände adaptiert und begriffsanalytisch, d. h. mit Hilfe von Kontexten formuliert. Ein Ziel dieser Diplomarbeit ist es, die Konstruktion des Gerüstes eines Begriffsverbandes aus einem Kontext heraus beschreiben zu können. Die Anwendbarkeit des Gerüstes wird dabei von vollständigen Verbänden endlicher Länge auf doppelt fundierte vollständige Verbände (bzw. deren reduzierte Kontexte) erweitert. Im zweiten Teil der Arbeit wird die von M_3 erzeugte Varietät betrachtet. Die darin enthaltenen doppelt fundierten vollständigen Verbände werden anhand ihrer reduzierten Kontexte charakterisiert. - 1.Atzmueller, M., Lemmerich, F., Krause, B., Hotho, A.: Spammer Discrimination: Discovering Local Patterns for Concept Characterization and Description. In: Fürnkranz, J. and Knobbe, A. (eds.) Proc. LeGo-09: From Local Patterns to Global Models, Workshop at the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. , Bled, Slovenia (2009).
@inproceedings{atzmueller09,
address = {Bled, Slovenia},
author = {Atzmueller, Martin and Lemmerich, Florian and Krause, Beate and Hotho, Andreas},
booktitle = {Proc. LeGo-09: From Local Patterns to Global Models, Workshop at the 2009 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
editor = {Fürnkranz, Johannes and Knobbe, Arno},
keywords = {relevancy},
month = {09},
note = {accepted},
title = {Spammer Discrimination: Discovering Local Patterns for Concept Characterization and Description},
year = 2009
}%0 Conference Paper
%1 atzmueller09
%A Atzmueller, Martin
%A Lemmerich, Florian
%A Krause, Beate
%A Hotho, Andreas
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%C Bled, Slovenia
%D 2009
%E Fürnkranz, Johannes
%E Knobbe, Arno
%T Spammer Discrimination: Discovering Local Patterns for Concept Characterization and Description - 1.Benz, D., Eisterlehner, F., Hotho, A., Jäschke, R., Krause, B., Stumme, G.: Managing publications and bookmarks with BibSonomy. In: Cattuto, C., Ruffo, G., and Menczer, F. (eds.) HT ’09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia. pp. 323–324. ACM, New York, NY, USA (2009). https://doi.org/10.1145/1557914.1557969.In this demo we present BibSonomy, a social bookmark and publication sharing system.
@inproceedings{benz2009managing,
abstract = {In this demo we present BibSonomy, a social bookmark and publication sharing system.},
address = {New York, NY, USA},
author = {Benz, Dominik and Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd},
booktitle = {HT '09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia},
editor = {Cattuto, Ciro and Ruffo, Giancarlo and Menczer, Filippo},
keywords = {itegpub},
month = {06},
pages = {323--324},
publisher = {ACM},
title = {Managing publications and bookmarks with BibSonomy},
year = 2009
}%0 Conference Paper
%1 benz2009managing
%A Benz, Dominik
%A Eisterlehner, Folke
%A Hotho, Andreas
%A Jäschke, Robert
%A Krause, Beate
%A Stumme, Gerd
%B HT '09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia
%C New York, NY, USA
%D 2009
%E Cattuto, Ciro
%E Ruffo, Giancarlo
%E Menczer, Filippo
%I ACM
%P 323--324
%R 10.1145/1557914.1557969
%T Managing publications and bookmarks with BibSonomy
%U http://portal.acm.org/citation.cfm?doid=1557914.1557969#
%X In this demo we present BibSonomy, a social bookmark and publication sharing system.
%@ 978-1-60558-486-7 - 1.Jäschke, R., Eisterlehner, F., Hotho, A., Stumme, G.: Testing and Evaluating Tag Recommenders in a Live System. In: Benz, D. and Janssen, F. (eds.) Workshop on Knowledge Discovery, Data Mining, and Machine Learning. pp. 44–51 (2009).The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.
@inproceedings{jaeschke2009testingKDML,
abstract = {The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.},
author = {Jäschke, Robert and Eisterlehner, Folke and Hotho, Andreas and Stumme, Gerd},
booktitle = {Workshop on Knowledge Discovery, Data Mining, and Machine Learning},
editor = {Benz, Dominik and Janssen, Frederik},
keywords = {bibsonomy},
month = {09},
pages = {44--51},
title = {Testing and Evaluating Tag Recommenders in a Live System},
year = 2009
}%0 Conference Paper
%1 jaeschke2009testingKDML
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%A Eisterlehner, Folke
%A Hotho, Andreas
%A Stumme, Gerd
%B Workshop on Knowledge Discovery, Data Mining, and Machine Learning
%D 2009
%E Benz, Dominik
%E Janssen, Frederik
%P 44--51
%T Testing and Evaluating Tag Recommenders in a Live System
%U http://lwa09.informatik.tu-darmstadt.de/pub/KDML/WebHome/kdml09_R.Jaeschke_et_al.pdf
%X The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework. - 1.Eisterlehner, F., Hotho, A., Jäschke, R. eds.: ECML PKDD Discovery Challenge 2009 (DC09). (2009).
@proceedings{eisterlehner2009ecmlpkdd,
editor = {Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert},
keywords = {pkdd},
month = {09},
series = {CEUR-WS.org},
title = {ECML PKDD Discovery Challenge 2009 (DC09)},
volume = 497,
year = 2009
}%0 Conference Proceedings
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%B CEUR-WS.org
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%E Eisterlehner, Folke
%E Hotho, Andreas
%E Jäschke, Robert
%T ECML PKDD Discovery Challenge 2009 (DC09)
%U http://ceur-ws.org/Vol-497
%V 497 - 1.Benz, D., Krause, B., Kumar, G.P., Hotho, A., Stumme, G.: Characterizing Semantic Relatedness of Search Query Terms. In: Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009). , Bled, Slovenia (2009).
@inproceedings{benz2009characterizing,
address = {Bled, Slovenia},
author = {Benz, Dominik and Krause, Beate and Kumar, G. Praveen and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009)},
keywords = {pkdd},
month = {09},
title = {Characterizing Semantic Relatedness of Search Query Terms},
year = 2009
}%0 Conference Paper
%1 benz2009characterizing
%A Benz, Dominik
%A Krause, Beate
%A Kumar, G. Praveen
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009)
%C Bled, Slovenia
%D 2009
%T Characterizing Semantic Relatedness of Search Query Terms - 1.Atzmüller, M., Lemmerich, F., Krause, B., Hotho, A.: Who are the Spammers - Understandable Local Patterns for Concept Description. In: 7th Conference on Computer Methods and Systems. , Krakow, Poland (2009).
@inproceedings{atze09,
address = {Krakow, Poland},
author = {Atzmüller, Martin and Lemmerich, Florian and Krause, Beate and Hotho, Andreas},
booktitle = {7th Conference on Computer Methods and Systems},
keywords = {spam},
month = 11,
note = {ISBN 83-916420-5-4},
title = {Who are the Spammers - Understandable Local Patterns for Concept Description},
year = 2009
}%0 Conference Paper
%1 atze09
%A Atzmüller, Martin
%A Lemmerich, Florian
%A Krause, Beate
%A Hotho, Andreas
%B 7th Conference on Computer Methods and Systems
%C Krakow, Poland
%D 2009
%T Who are the Spammers - Understandable Local Patterns for Concept Description
%U http://www.cms.agh.edu.pl/ - 1.Atzmueller, M., Lemmerich, F., Krause, B., Hotho, A.: Who are the Spammers? Understandable Local Patterns for Concept Description. In: 7th Conference on Computer Methods and Systems. , Krakow, Poland (2009).
@inproceedings{atze09,
address = {Krakow, Poland},
author = {Atzmueller, Martin and Lemmerich, Florian and Krause, Beate and Hotho, Andreas},
booktitle = {7th Conference on Computer Methods and Systems},
keywords = {bibsonomy},
month = 11,
note = {ISBN 83-916420-5-4},
title = {Who are the Spammers? Understandable Local Patterns for Concept Description},
year = 2009
}%0 Conference Paper
%1 atze09
%A Atzmueller, Martin
%A Lemmerich, Florian
%A Krause, Beate
%A Hotho, Andreas
%B 7th Conference on Computer Methods and Systems
%C Krakow, Poland
%D 2009
%T Who are the Spammers? Understandable Local Patterns for Concept Description
%U http://www.cms.agh.edu.pl/
2008
- 1.Jäschke, R., Krause, B., Hotho, A., Stumme, G.: Logsonomy — A Search Engine Folksonomy. In: Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008). AAAI Press (2008).In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.
@inproceedings{Jaeschke2008logsonomy,
abstract = {In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.},
author = {Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)},
keywords = {search},
publisher = {AAAI Press},
title = {Logsonomy — A Search Engine Folksonomy},
year = 2008
}%0 Conference Paper
%1 Jaeschke2008logsonomy
%A Jäschke, Robert
%A Krause, Beate
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)
%D 2008
%I AAAI Press
%T Logsonomy — A Search Engine Folksonomy
%U https://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf
%X In social bookmarking systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Search engines filter the vast information of the web. Queries describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us. - 1.Hotho, A., Benz, D., Jäschke, R., Krause, B. eds.: ECML PKDD Discovery Challenge 2008 (RSDC’08). Workshop at 18th Europ. Conf. on Machine Learning (ECML’08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’08) (2008).
@book{hotho2008challenge,
editor = {Hotho, Andreas and Benz, Dominik and Jäschke, Robert and Krause, Beate},
keywords = {PKDD},
publisher = {Workshop at 18th Europ. Conf. on Machine Learning (ECML'08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'08)},
title = {ECML PKDD Discovery Challenge 2008 (RSDC'08)},
year = 2008
}%0 Book
%1 hotho2008challenge
%D 2008
%E Hotho, Andreas
%E Benz, Dominik
%E Jäschke, Robert
%E Krause, Beate
%I Workshop at 18th Europ. Conf. on Machine Learning (ECML'08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'08)
%T ECML PKDD Discovery Challenge 2008 (RSDC'08)
%U https://www.kde.cs.uni-kassel.de/ws/rsdc08/pdf/all_rsdc_v2.pdf - 1.Jäschke, R., Hotho, A., Schmitz, C., Ganter, B., Stumme, G.: Discovering Shared Conceptualizations in Folksonomies. Web Semantics: Science, Services and Agents on the World Wide Web. 6, 38–53 (2008).Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.
@article{jaeschke2008discovering,
abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.},
author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
booktitle = {Semantic Web and Web 2.0},
journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
keywords = {bibsonomy},
month = {02},
number = 1,
pages = {38--53},
title = {Discovering Shared Conceptualizations in Folksonomies},
volume = 6,
year = 2008
}%0 Journal Article
%1 jaeschke2008discovering
%A Jäschke, Robert
%A Hotho, Andreas
%A Schmitz, Christoph
%A Ganter, Bernhard
%A Stumme, Gerd
%B Semantic Web and Web 2.0
%D 2008
%J Web Semantics: Science, Services and Agents on the World Wide Web
%N 1
%P 38--53
%T Discovering Shared Conceptualizations in Folksonomies
%U http://www.sciencedirect.com/science/article/B758F-4R53WD4-1/2/ae56bd6e7132074272ca2035be13781b
%V 6
%X Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples. - 1.Jäschke, R., Marinho, L., Hotho, A., Schmidt-Thieme, L., Stumme, G.: Tag Recommendations in Social Bookmarking Systems. AI Communications. 21, 231–247 (2008). https://doi.org/10.3233/AIC-2008-0438.Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
@article{jaeschke2008tag,
abstract = {Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.},
address = {Amsterdam},
author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
editor = {Giunchiglia, Enrico},
journal = {AI Communications},
keywords = {selected},
month = 12,
number = 4,
pages = {231--247},
publisher = {IOS Press},
title = {Tag Recommendations in Social Bookmarking Systems},
volume = 21,
year = 2008
}%0 Journal Article
%1 jaeschke2008tag
%A Jäschke, Robert
%A Marinho, Leandro
%A Hotho, Andreas
%A Schmidt-Thieme, Lars
%A Stumme, Gerd
%C Amsterdam
%D 2008
%E Giunchiglia, Enrico
%I IOS Press
%J AI Communications
%N 4
%P 231--247
%R 10.3233/AIC-2008-0438
%T Tag Recommendations in Social Bookmarking Systems
%U https://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2008tag.pdf
%V 21
%X Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender. - 1.Krause, B., Schmitz, C., Hotho, A., Stumme, G.: The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems. In: AIRWeb ’08: Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web. pp. 61–68. ACM, Beijing, China (2008). https://doi.org/10.1145/1451983.1451998.The annotation of web sites in social bookmarking systemshas become a popular way to manage and find informationon the web. The community structure of such systems attractsspammers: recent post pages, popular pages or specifictag pages can be manipulated easily. As a result, searchingor tracking recent posts does not deliver quality resultsannotated in the community, but rather unsolicited, oftencommercial, web sites. To retain the benefits of sharingone’s web content, spam-fighting mechanisms that can facethe flexible strategies of spammers need to be developed.
@inproceedings{krause2008antisocial,
abstract = {The annotation of web sites in social bookmarking systemshas become a popular way to manage and find informationon the web. The community structure of such systems attractsspammers: recent post pages, popular pages or specifictag pages can be manipulated easily. As a result, searchingor tracking recent posts does not deliver quality resultsannotated in the community, but rather unsolicited, oftencommercial, web sites. To retain the benefits of sharingone’s web content, spam-fighting mechanisms that can facethe flexible strategies of spammers need to be developed.},
address = {New York, NY, USA},
author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd},
booktitle = {AIRWeb '08: Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web},
keywords = {summer},
month = {04},
pages = {61--68},
publisher = {ACM},
title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems},
year = 2008
}%0 Conference Paper
%1 krause2008antisocial
%A Krause, Beate
%A Schmitz, Christoph
%A Hotho, Andreas
%A Stumme, Gerd
%B AIRWeb '08: Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web
%C New York, NY, USA
%D 2008
%I ACM
%P 61--68
%R 10.1145/1451983.1451998
%T The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems
%U http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf
%X The annotation of web sites in social bookmarking systemshas become a popular way to manage and find informationon the web. The community structure of such systems attractsspammers: recent post pages, popular pages or specifictag pages can be manipulated easily. As a result, searchingor tracking recent posts does not deliver quality resultsannotated in the community, but rather unsolicited, oftencommercial, web sites. To retain the benefits of sharingone’s web content, spam-fighting mechanisms that can facethe flexible strategies of spammers need to be developed.
%@ 978-1-60558-159-0 - 1.Benz, D., Grobelnik, M., Hotho, A., Jäschke, R., Mladenic, D., Servedio, V.D.P., Sizov, S., Szomszor, M.: Analyzing Tag Semantics Across Collaborative Tagging Systems. In: Alani, H., Staab, S., and Stumme, G. (eds.) Social Web Communities. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany (2008).The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.
@inproceedings{benz2008analyzing,
abstract = {The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.},
address = {Dagstuhl, Germany},
author = {Benz, Dominik and Grobelnik, Marko and Hotho, Andreas and Jäschke, Robert and Mladenic, Dunja and Servedio, Vito D. P. and Sizov, Sergej and Szomszor, Martin},
booktitle = {Social Web Communities},
editor = {Alani, Harith and Staab, Steffen and Stumme, Gerd},
keywords = {dagstuhl},
month = {09},
number = {08391},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik},
series = {Dagstuhl Seminar Proceedings},
title = {Analyzing Tag Semantics Across Collaborative Tagging Systems},
year = 2008
}%0 Conference Paper
%1 benz2008analyzing
%A Benz, Dominik
%A Grobelnik, Marko
%A Hotho, Andreas
%A Jäschke, Robert
%A Mladenic, Dunja
%A Servedio, Vito D. P.
%A Sizov, Sergej
%A Szomszor, Martin
%B Social Web Communities
%C Dagstuhl, Germany
%D 2008
%E Alani, Harith
%E Staab, Steffen
%E Stumme, Gerd
%I Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik
%N 08391
%T Analyzing Tag Semantics Across Collaborative Tagging Systems
%U http://drops.dagstuhl.de/opus/volltexte/2008/1785
%X The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance. - 1.Cattuto, C., Benz, D., Hotho, A., Stumme, G.: Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems. In: Proceedings of the 3rd Workshop on Ontology Learning and Population (OLP3). pp. 39–43. , Patras, Greece (2008).Social bookmarking systems allow users to organise collections of resources on the Web in a collaborative fashion. The increasing popularity of these systems as well as first insights into their emergent semantics have made them relevant to disciplines like knowledge extraction and ontology learning. The problem of devising methods to measure the semantic relatedness between tags and characterizing it semantically is still largely open. Here we analyze three measures of tag relatedness: tag co-occurrence, cosine similarity of co-occurrence distributions, and FolkRank, an adaptation of the PageRank algorithm to folksonomies. Each measure is computed on tags from a large-scale dataset crawled from the social bookmarking system del.icio.us. To provide a semantic grounding of our findings, a connection to WordNet (a semantic lexicon for the English language) is established by mapping tags into synonym sets of WordNet, and applying there well-known metrics of semantic similarity. Our results clearly expose different characteristics of the selected measures of relatedness, making them applicable to different subtasks of knowledge extraction such as synonym detection or discovery of concept hierarchies.
@inproceedings{cattuto2008semantic,
abstract = {Social bookmarking systems allow users to organise collections of resources on the Web in a collaborative fashion. The increasing popularity of these systems as well as first insights into their emergent semantics have made them relevant to disciplines like knowledge extraction and ontology learning. The problem of devising methods to measure the semantic relatedness between tags and characterizing it semantically is still largely open. Here we analyze three measures of tag relatedness: tag co-occurrence, cosine similarity of co-occurrence distributions, and FolkRank, an adaptation of the PageRank algorithm to folksonomies. Each measure is computed on tags from a large-scale dataset crawled from the social bookmarking system del.icio.us. To provide a semantic grounding of our findings, a connection to WordNet (a semantic lexicon for the English language) is established by mapping tags into synonym sets of WordNet, and applying there well-known metrics of semantic similarity. Our results clearly expose different characteristics of the selected measures of relatedness, making them applicable to different subtasks of knowledge extraction such as synonym detection or discovery of concept hierarchies.},
address = {Patras, Greece},
author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {Proceedings of the 3rd Workshop on Ontology Learning and Population (OLP3)},
keywords = {itegpub},
month = {07},
note = {ISBN 978-960-89282-6-8},
pages = {39--43},
title = {Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems},
year = 2008
}%0 Conference Paper
%1 cattuto2008semantic
%A Cattuto, Ciro
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B Proceedings of the 3rd Workshop on Ontology Learning and Population (OLP3)
%C Patras, Greece
%D 2008
%P 39--43
%T Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems
%U https://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2008semantic.pdf
%X Social bookmarking systems allow users to organise collections of resources on the Web in a collaborative fashion. The increasing popularity of these systems as well as first insights into their emergent semantics have made them relevant to disciplines like knowledge extraction and ontology learning. The problem of devising methods to measure the semantic relatedness between tags and characterizing it semantically is still largely open. Here we analyze three measures of tag relatedness: tag co-occurrence, cosine similarity of co-occurrence distributions, and FolkRank, an adaptation of the PageRank algorithm to folksonomies. Each measure is computed on tags from a large-scale dataset crawled from the social bookmarking system del.icio.us. To provide a semantic grounding of our findings, a connection to WordNet (a semantic lexicon for the English language) is established by mapping tags into synonym sets of WordNet, and applying there well-known metrics of semantic similarity. Our results clearly expose different characteristics of the selected measures of relatedness, making them applicable to different subtasks of knowledge extraction such as synonym detection or discovery of concept hierarchies.
%@ 978-960-89282-6-8 - 1.Alani, H., Staab, S., Stumme, G. eds.: Proceedings of the Dagstuhl Seminar on Social Web Communities. Schloss Dagstuhl (2008).
@book{alani2008proceedings,
editor = {Alani, Harith and Staab, Steffen and Stumme, Gerd},
keywords = {itegpub},
month = {09},
publisher = {Schloss Dagstuhl},
title = {Proceedings of the Dagstuhl Seminar on Social Web Communities},
year = 2008
}%0 Book
%1 alani2008proceedings
%D 2008
%E Alani, Harith
%E Staab, Steffen
%E Stumme, Gerd
%I Schloss Dagstuhl
%T Proceedings of the Dagstuhl Seminar on Social Web Communities
%U http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=08391 - 1.Cattuto, C., Benz, D., Hotho, A., Stumme, G.: Semantic Grounding of Tag Relatedness in Social Bookmarking Systems. In: Sheth, A.P., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T.W., and Thirunarayan, K. (eds.) The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008. pp. 615–631. Springer, Heidelberg (2008). https://doi.org/http://dx.doi.org/10.1007/978-3-540-88564-1_39.Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For taskslike synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.
@inproceedings{cattuto2008semantica,
abstract = {Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For taskslike synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.},
address = {Heidelberg},
author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
booktitle = {The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008},
editor = {Sheth, Amit P. and Staab, Steffen and Dean, Mike and Paolucci, Massimo and Maynard, Diana and Finin, Timothy W. and Thirunarayan, Krishnaprasad},
keywords = {methods_concepthierarchy},
pages = {615--631},
publisher = {Springer},
series = {LNAI},
title = {Semantic Grounding of Tag Relatedness in Social Bookmarking Systems},
volume = 5318,
year = 2008
}%0 Conference Paper
%1 cattuto2008semantica
%A Cattuto, Ciro
%A Benz, Dominik
%A Hotho, Andreas
%A Stumme, Gerd
%B The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008
%C Heidelberg
%D 2008
%E Sheth, Amit P.
%E Staab, Steffen
%E Dean, Mike
%E Paolucci, Massimo
%E Maynard, Diana
%E Finin, Timothy W.
%E Thirunarayan, Krishnaprasad
%I Springer
%P 615--631
%R http://dx.doi.org/10.1007/978-3-540-88564-1_39
%T Semantic Grounding of Tag Relatedness in Social Bookmarking Systems
%U https://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2008semantica.pdf
%V 5318
%X Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For taskslike synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application. - 1.Krause, B., Hotho, A., Stumme, G.: A Comparison of Social Bookmarking with Traditional Search. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., and White, R.W. (eds.) 30th European Conference on IR Research, ECIR 2008. pp. 101–113. Springer, Glasgow, UK (2008).
@inproceedings{krause08social,
address = {Glasgow, UK},
author = {Krause, Beate and Hotho, Andreas and Stumme, Gerd},
booktitle = {30th European Conference on IR Research, ECIR 2008},
editor = {Macdonald, Craig and Ounis, Iadh and Plachouras, Vassilis and Ruthven, Ian and White, Ryen W.},
keywords = {bookmarking},
month = {04},
pages = {101-113},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {A Comparison of Social Bookmarking with Traditional Search},
volume = 4956,
year = 2008
}%0 Conference Paper
%1 krause08social
%A Krause, Beate
%A Hotho, Andreas
%A Stumme, Gerd
%B 30th European Conference on IR Research, ECIR 2008
%C Glasgow, UK
%D 2008
%E Macdonald, Craig
%E Ounis, Iadh
%E Plachouras, Vassilis
%E Ruthven, Ian
%E White, Ryen W.
%I Springer
%P 101-113
%T A Comparison of Social Bookmarking with Traditional Search
%V 4956
%@ 978-3-540-78645-0 - 1.Stefani, S.: Entwicklung modularer, wiederverwendbarer Simulationsbausteine zur Unterstützung von Hardware-in-the-Loop Tests eingebetteter Systeme im Maschinen- und Anlagenbau, http://www.svenstefani.de/publ/diplom2/da2-svenstefani.pdf, (2008).
@mastersthesis{uniksdiplom2,
address = {Kassel},
author = {Stefani, Sven},
editor = {Stefani, Sven},
keywords = {diplom},
month = {03},
school = {Universität Kassel},
title = {Entwicklung modularer, wiederverwendbarer Simulationsbausteine zur Unterstützung von Hardware-in-the-Loop Tests eingebetteter Systeme im Maschinen- und Anlagenbau},
year = 2008
}%0 Thesis
%1 uniksdiplom2
%A Stefani, Sven
%C Kassel
%D 2008
%E Stefani, Sven
%T Entwicklung modularer, wiederverwendbarer Simulationsbausteine zur Unterstützung von Hardware-in-the-Loop Tests eingebetteter Systeme im Maschinen- und Anlagenbau
%U http://www.svenstefani.de/publ/diplom2/da2-svenstefani.pdf - 1.Hotho, A.: Social Bookmarking. In: Back, A., Gronau, N., and Tochtermann, K. (eds.) Web 2.0 in der Unternehmenspraxis: Grundlagen, Fallstudien und Trends zum Einsatz von Social Software. pp. 26–38. Oldenbourg Verlag, München (2008).
@inbook{hotho2008bookmarking,
address = {München},
author = {Hotho, Andreas},
booktitle = {Web 2.0 in der Unternehmenspraxis: Grundlagen, Fallstudien und Trends zum Einsatz von Social Software},
editor = {Back, Andrea and Gronau, Norbert and Tochtermann, Klaus},
keywords = {bookmarking},
pages = {26-38},
publisher = {Oldenbourg Verlag},
title = {Social Bookmarking},
year = 2008
}%0 Book Section
%1 hotho2008bookmarking
%A Hotho, Andreas
%B Web 2.0 in der Unternehmenspraxis: Grundlagen, Fallstudien und Trends zum Einsatz von Social Software
%C München
%D 2008
%E Back, Andrea
%E Gronau, Norbert
%E Tochtermann, Klaus
%I Oldenbourg Verlag
%P 26-38
%T Social Bookmarking
%U http://www.amazon.de/gp/redirect.html%3FASIN=3486585797%26tag=ws%26lcode=xm2%26cID=2025%26ccmID=165953%26location=/Web-2-0-Unternehmenspraxis-Grundlagen-Fallstudien/dp/3486585797%253FSubscriptionId=13CT5CVB80YFWJEPWS02
%@ 9783486585797 - 1.Krause, B., Jäschke, R., Hotho, A., Stumme, G.: Logsonomy - Social Information Retrieval with Logdata. In: HT ’08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia. pp. 157–166. ACM, Pittsburgh, PA, USA (2008). https://doi.org/10.1145/1379092.1379123.Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today’s search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.
@inproceedings{krause2008logsonomy,
abstract = {Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today’s search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.},
address = {New York, NY, USA},
author = {Krause, Beate and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
booktitle = {HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia},
keywords = {information},
pages = {157--166},
publisher = {ACM},
title = {Logsonomy - Social Information Retrieval with Logdata},
year = 2008
}%0 Conference Paper
%1 krause2008logsonomy
%A Krause, Beate
%A Jäschke, Robert
%A Hotho, Andreas
%A Stumme, Gerd
%B HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia
%C New York, NY, USA
%D 2008
%I ACM
%P 157--166
%R 10.1145/1379092.1379123
%T Logsonomy - Social Information Retrieval with Logdata
%U https://www.kde.cs.uni-kassel.de/pub/pdf/krause2008logsonomy.pdf
%X Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today’s search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.
%@ 978-1-59593-985-2 - 1.Macek, B.-E.: Synopsen-Sharing zur effizienten Anfrageverarbeitung in Datenströmen. (2008).
@article{macek2008synopsensharing,
author = {Macek, Björn-Elmar},
keywords = {MyOwn},
title = {Synopsen-Sharing zur effizienten Anfrageverarbeitung in Datenströmen},
year = 2008
}%0 Journal Article
%1 macek2008synopsensharing
%A Macek, Björn-Elmar
%D 2008
%T Synopsen-Sharing zur effizienten Anfrageverarbeitung in Datenströmen - 1.Illig, J.: Machine Learnability Analysis of Textclassifications in a Social Bookmarking Folksonomy, (2008).Social-bookmarking systems such as del.icio.us let users label resources with freely chosen key- words that they find most useful for their intentions. These keywords are also known as tags. The cumulated information from tag assignments by a large community of users constitutes a folksonomy. This thesis analyses how well tag assignments in a folksonomy, that are assigned to semistructured English texts can be found by automatic text classification systems. Therefore, the machine learning algorithms SVM, k-NN, multinomial naive Bayes, and Rocchio have been evaluated for their effectiveness with such data.
@mastersthesis{dipl1,
abstract = {Social-bookmarking systems such as del.icio.us let users label resources with freely chosen key- words that they find most useful for their intentions. These keywords are also known as tags. The cumulated information from tag assignments by a large community of users constitutes a folksonomy. This thesis analyses how well tag assignments in a folksonomy, that are assigned to semistructured English texts can be found by automatic text classification systems. Therefore, the machine learning algorithms SVM, k-NN, multinomial naive Bayes, and Rocchio have been evaluated for their effectiveness with such data.},
address = {Kassel},
author = {Illig, Jens},
keywords = {bookmarking},
school = {University of Kassel},
title = {Machine Learnability Analysis of Textclassifications in a Social Bookmarking Folksonomy},
type = {Bachelor Thesis},
year = 2008
}%0 Thesis
%1 dipl1
%A Illig, Jens
%C Kassel
%D 2008
%T Machine Learnability Analysis of Textclassifications in a Social Bookmarking Folksonomy
%X Social-bookmarking systems such as del.icio.us let users label resources with freely chosen key- words that they find most useful for their intentions. These keywords are also known as tags. The cumulated information from tag assignments by a large community of users constitutes a folksonomy. This thesis analyses how well tag assignments in a folksonomy, that are assigned to semistructured English texts can be found by automatic text classification systems. Therefore, the machine learning algorithms SVM, k-NN, multinomial naive Bayes, and Rocchio have been evaluated for their effectiveness with such data. - 1.J{ä}schke, R., Hotho, A., Schmitz, C., Ganter, B., Stumme, G.: Discovering shared conceptualizations in folksonomies. Web Semant. 6, 38–53 (2008). https://doi.org/http://dx.doi.org/10.1016/j.websem.2007.11.004.Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.
@article{1346701,
abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.},
address = {Amsterdam, The Netherlands, The Netherlands},
author = {J{ä}schke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
journal = {Web Semant.},
keywords = {analysis},
number = 1,
pages = {38--53},
publisher = {Elsevier Science Publishers B. V.},
title = {Discovering shared conceptualizations in folksonomies},
volume = 6,
year = 2008
}%0 Journal Article
%1 1346701
%A J{ä}schke, Robert
%A Hotho, Andreas
%A Schmitz, Christoph
%A Ganter, Bernhard
%A Stumme, Gerd
%C Amsterdam, The Netherlands, The Netherlands
%D 2008
%I Elsevier Science Publishers B. V.
%J Web Semant.
%N 1
%P 38--53
%R http://dx.doi.org/10.1016/j.websem.2007.11.004
%T Discovering shared conceptualizations in folksonomies
%U http://portal.acm.org/citation.cfm?id=1346701
%V 6
%X Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples. - 1.Brulic, S., Brulic, S., Deppe, P., Eschweiler, D., Etemadi, R., Herbold, K., Konersmann, C., Meiche, R., Scholz, C., Timm, N., Uckermann, A., Weber, E., Zorn, R.C.: CSI: PC2 - A High Performance Biometrie System. In: Informatiktage. pp. 209–212. GI (2008).
@inproceedings{DBLP:conf/informatiktage/BrulicBDEEHKMSTUWZ08,
author = {Brulic, Samir and Brulic, Samira and Deppe, Pascal and Eschweiler, Dominic and Etemadi, Rosbeh and Herbold, Klaus and Konersmann, Christian and Meiche, Robert and Scholz, Christoph and Timm, Nils and Uckermann, Andre and Weber, Elmar and Zorn, Rene C.},
booktitle = {Informatiktage},
crossref = {DBLP:conf/informatiktage/2008},
keywords = {pc2},
pages = {209-212},
publisher = {GI},
series = {LNI},
title = {CSI: PC2 - A High Performance Biometrie System},
volume = {S-6},
year = 2008
}%0 Conference Paper
%1 DBLP:conf/informatiktage/BrulicBDEEHKMSTUWZ08
%A Brulic, Samir
%A Brulic, Samira
%A Deppe, Pascal
%A Eschweiler, Dominic
%A Etemadi, Rosbeh
%A Herbold, Klaus
%A Konersmann, Christian
%A Meiche, Robert
%A Scholz, Christoph
%A Timm, Nils
%A Uckermann, Andre
%A Weber, Elmar
%A Zorn, Rene C.
%B Informatiktage
%D 2008
%I GI
%P 209-212
%T CSI: PC2 - A High Performance Biometrie System
%V S-6
%@ 978-3-88579-440-0 - 1.Völker, J., Vrandečić, D., Sure, Y., Hotho, A.: AEON - An approach to the automatic evaluation of ontologies. Applied Ontology. 3, 41–62 (2008).OntoClean is an approach towards the formal evaluation of taxonomic relations in ontologies. The application of OntoClean consists of two main steps. First, concepts are tagged according to meta-properties known as rigidity, unity, dependency and identity. Second, the tagged concepts are checked according to predefined constraints to discover taxonomic errors. Although OntoClean is well documented in numerous publications, it is still used rather infrequently due to the high costs of application. Especially, the manual tagging of concepts with the correct meta-properties requires substantial efforts of highly experienced ontology engineers. In order to facilitate the use of OntoClean and to enable the evaluation of real-world ontologies, we provide AEON, a tool which automatically tags concepts with appropriate OntoClean meta-properties and performs the constraint checking. We use the Web as an embodiment of world knowledge, where we search for patterns that indicate how to properly tag concepts. We thoroughly evaluated our approach against a manually created gold standard. The evaluation shows the competitiveness of our approach while at the same time significantly lowering the costs. All of our results, i.e. the tool AEON as well as the experiment data, are publicly available.
@article{voelker2008aeon,
abstract = {OntoClean is an approach towards the formal evaluation of taxonomic relations in ontologies. The application of OntoClean consists of two main steps. First, concepts are tagged according to meta-properties known as rigidity, unity, dependency and identity. Second, the tagged concepts are checked according to predefined constraints to discover taxonomic errors. Although OntoClean is well documented in numerous publications, it is still used rather infrequently due to the high costs of application. Especially, the manual tagging of concepts with the correct meta-properties requires substantial efforts of highly experienced ontology engineers. In order to facilitate the use of OntoClean and to enable the evaluation of real-world ontologies, we provide AEON, a tool which automatically tags concepts with appropriate OntoClean meta-properties and performs the constraint checking. We use the Web as an embodiment of world knowledge, where we search for patterns that indicate how to properly tag concepts. We thoroughly evaluated our approach against a manually created gold standard. The evaluation shows the competitiveness of our approach while at the same time significantly lowering the costs. All of our results, i.e. the tool AEON as well as the experiment data, are publicly available.},
address = {Amsterdam, The Netherlands, The Netherlands},
author = {Völker, Johanna and Vrandečić, Denny and Sure, York and Hotho, Andreas},
journal = {Applied Ontology},
keywords = {ontology},
number = {1-2},
pages = {41--62},
publisher = {IOS Press},
title = {AEON - An approach to the automatic evaluation of ontologies},
volume = 3,
year = 2008
}%0 Journal Article
%1 voelker2008aeon
%A Völker, Johanna
%A Vrandečić, Denny
%A Sure, York
%A Hotho, Andreas
%C Amsterdam, The Netherlands, The Netherlands
%D 2008
%I IOS Press
%J Applied Ontology
%N 1-2
%P 41--62
%T AEON - An approach to the automatic evaluation of ontologies
%U http://portal.acm.org/citation.cfm?id=1412422
%V 3
%X OntoClean is an approach towards the formal evaluation of taxonomic relations in ontologies. The application of OntoClean consists of two main steps. First, concepts are tagged according to meta-properties known as rigidity, unity, dependency and identity. Second, the tagged concepts are checked according to predefined constraints to discover taxonomic errors. Although OntoClean is well documented in numerous publications, it is still used rather infrequently due to the high costs of application. Especially, the manual tagging of concepts with the correct meta-properties requires substantial efforts of highly experienced ontology engineers. In order to facilitate the use of OntoClean and to enable the evaluation of real-world ontologies, we provide AEON, a tool which automatically tags concepts with appropriate OntoClean meta-properties and performs the constraint checking. We use the Web as an embodiment of world knowledge, where we search for patterns that indicate how to properly tag concepts. We thoroughly evaluated our approach against a manually created gold standard. The evaluation shows the competitiveness of our approach while at the same time significantly lowering the costs. All of our results, i.e. the tool AEON as well as the experiment data, are publicly available. - 1.May, M., Berendt, B., Cornuéjols, A., Gama, J., Giannotti, F., Hotho, A., Malerba, D., Menesalvas, E., Morik, K., Pedersen, R., Saitta, L., Saygin, Y., Schuster, A., Vanhoof, K.: Research Challenges in Ubiquitous Knowledge Discovery. In: Next Generation of Data Mining (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series). Chapman & Hall/CRC (2008).
@incollection{1420085867,
author = {May, Michael and Berendt, Bettina and Cornuéjols, Antoine and Gama, Jõao and Giannotti, Fosca and Hotho, Andreas and Malerba, Donato and Menesalvas, Ernestina and Morik, Katharina and Pedersen, Rasmus and Saitta, Lorenza and Saygin, Yücel and Schuster, Assaf and Vanhoof, Koen},
booktitle = {Next Generation of Data Mining (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)},
edition = 1,
keywords = {kdd},
publisher = {Chapman & Hall/CRC},
title = {Research Challenges in Ubiquitous Knowledge Discovery},
year = 2008
}%0 Book Section
%1 1420085867
%A May, Michael
%A Berendt, Bettina
%A Cornuéjols, Antoine
%A Gama, Jõao
%A Giannotti, Fosca
%A Hotho, Andreas
%A Malerba, Donato
%A Menesalvas, Ernestina
%A Morik, Katharina
%A Pedersen, Rasmus
%A Saitta, Lorenza
%A Saygin, Yücel
%A Schuster, Assaf
%A Vanhoof, Koen
%B Next Generation of Data Mining (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)
%D 2008
%I Chapman & Hall/CRC
%T Research Challenges in Ubiquitous Knowledge Discovery
%U http://208.254.79.11/shopping_cart/products/product_contents.asp?id=&parent_id=497&sku=C5867&isbn=9781420085860&pc=
%7 1
%@ 1420085867 - 1.Berendt, B., Glance, N., Hotho, A. eds.: Wikis, Blogs, Bookmarking Tools - Mining the Web 2.0 Workshop. Workshop at 18th Europ. Conf. on Machine Learning (ECML’08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’08) (2008).
@book{berendt2008challenge,
editor = {Berendt, Bettina and Glance, Natalie and Hotho, Andreas},
keywords = {blog},
publisher = {Workshop at 18th Europ. Conf. on Machine Learning (ECML'08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'08)},
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%T Wikis, Blogs, Bookmarking Tools - Mining the Web 2.0 Workshop
%U https://www.kde.cs.uni-kassel.de/ws/wbbtmine2008/pdf/all_wbbtmine2008.pdf - 1.Bade, K., Benz, D.: Evaluation Strategies for Learning Algorithms of Hierarchical Structures. In: Proceedings of the 32nd Annual Conference of the German Classification Society - Advances in Data Analysis, Data Handling and Business Intelligence (GfKl 2008). Springer, Berlin-Heidelberg (2008).Several learning tasks comprise hierarchies. Comparison with a "goldstandard" is often performed to evaluate the quality of a learned hierarchy. We assembled various similarity metrics that have been proposed in different disciplines and compared them in a unified interdisciplinary framework for hierarchical evaluation which is based on the distinction of three fundamental dimensions. Identifying deficiencies for measuring structural similarity, we suggest three new measures for this purpose, either extending existing ones or based on new ideas. Experiments with an artificial dataset were performed to compare the different measures. As shown by our results, the measures vary greatly in their properties.
@inproceedings{bade2008evaluation,
abstract = {Several learning tasks comprise hierarchies. Comparison with a "goldstandard" is often performed to evaluate the quality of a learned hierarchy. We assembled various similarity metrics that have been proposed in different disciplines and compared them in a unified interdisciplinary framework for hierarchical evaluation which is based on the distinction of three fundamental dimensions. Identifying deficiencies for measuring structural similarity, we suggest three new measures for this purpose, either extending existing ones or based on new ideas. Experiments with an artificial dataset were performed to compare the different measures. As shown by our results, the measures vary greatly in their properties.},
address = {Berlin-Heidelberg},
author = {Bade, Korinna and Benz, Dominik},
booktitle = {Proceedings of the 32nd Annual Conference of the German Classification Society - Advances in Data Analysis, Data Handling and Business Intelligence (GfKl 2008)},
keywords = {itegpub},
note = {in press},
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title = {Evaluation Strategies for Learning Algorithms of Hierarchical Structures},
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%X Several learning tasks comprise hierarchies. Comparison with a "goldstandard" is often performed to evaluate the quality of a learned hierarchy. We assembled various similarity metrics that have been proposed in different disciplines and compared them in a unified interdisciplinary framework for hierarchical evaluation which is based on the distinction of three fundamental dimensions. Identifying deficiencies for measuring structural similarity, we suggest three new measures for this purpose, either extending existing ones or based on new ideas. Experiments with an artificial dataset were performed to compare the different measures. As shown by our results, the measures vary greatly in their properties.
2007
- 1.Cao, Y., Ehms, K., Fiedler, S., Hofer, M., Kaiamo, A.-K., Kieslinger, B., Klamma, R., Krause, B., Kravcik, M., Ryyppö, T., Spaniol, M., Stumme, G., Wild, F.: Case study on social software use in distributed working environments, http://www.prolearn-project.org/deliverables/view?id=1432, (2007).
@misc{cao07casestudy,
author = {Cao, Yiwei and Ehms, Karsten and Fiedler, Sebastian and Hofer, Margit and Kaiamo, Anna-Kaarina and Kieslinger, Barbara and Klamma, Ralf and Krause, Beate and Kravcik, Milos and Ryyppö, Tommi and Spaniol, Marc and Stumme, Gerd and Wild, Fridolin},
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%A Fiedler, Sebastian
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%A Stumme, Gerd
%A Wild, Fridolin
%D 2007
%T Case study on social software use in distributed working environments
%U http://www.prolearn-project.org/deliverables/view?id=1432 - 1.Catutto, C., Schmitz, C., Baldassarri, A., Servedio, V.D.P., Loreto, V., Hotho, and A., Grahl, M., Stumme, G.: Network Properties of Folksonomies. AI Communications Journal, Special Issue on "Network Analysis in Natural Sciences and Engineering". (2007).
@article{cattuto2007network,
author = {Catutto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and and Andreas Hotho and Grahl, Miranda and Stumme, Gerd},
editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen},
journal = {AI Communications Journal, Special Issue on "Network Analysis in Natural Sciences and Engineering"},
keywords = {collective},
publisher = {IOS Press},
title = {Network Properties of Folksonomies},
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}%0 Journal Article
%1 cattuto2007network
%A Catutto, Ciro
%A Schmitz, Christoph
%A Baldassarri, Andrea
%A Servedio, Vito D. P.
%A Loreto, Vittorio
%A Hotho, and Andreas
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%A Stumme, Gerd
%D 2007
%E Hoche, Susanne
%E Nürnberger, Andreas
%E Flach, Jürgen
%I IOS Press
%J AI Communications Journal, Special Issue on "Network Analysis in Natural Sciences and Engineering"
%T Network Properties of Folksonomies - 1.Jaeschke, R., Marinho, L., Hotho, A., Schmidt-Thieme, L., Stumme, G.: Tag Recommendations in Folksonomies. In: Hinneburg, A. (ed.) Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007). pp. 13–20. Martin-Luther-Universität Halle-Wittenberg (2007).
@inproceedings{jaeschke07tagKdml,
author = {Jaeschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
booktitle = {Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)},
editor = {Hinneburg, Alexander},
keywords = {bookmarking},
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}%0 Conference Paper
%1 jaeschke07tagKdml
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%A Marinho, Leandro
%A Hotho, Andreas
%A Schmidt-Thieme, Lars
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%B Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)
%D 2007
%E Hinneburg, Alexander
%I Martin-Luther-Universität Halle-Wittenberg
%P 13-20
%T Tag Recommendations in Folksonomies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2007/jaeschke07tagrecommendationsKDML.pdf
%@ 978-3-86010-907-6 - 1.Schmitz, C.: Self-Organized Collaborative Knowledge Management, http://www.uni-kassel.de/upress/online/frei/978-3-89958-325-0.volltext.frei.pdf, (2007).
@phdthesis{schmitz2007self,
author = {Schmitz, Christoph},
keywords = {peertopeer},
month = {09},
pages = 217,
publisher = {Kassel University Press},
school = {Universität Kassel},
title = {Self-Organized Collaborative Knowledge Management},
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}%0 Thesis
%1 schmitz2007self
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%I Kassel University Press
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%U http://www.uni-kassel.de/upress/online/frei/978-3-89958-325-0.volltext.frei.pdf
%@ 978-3-89958-325-0 - 1.Benz, D., Hotho, A.: Position Paper: Ontology Learning from Folksonomies. In: Hinneburg, A. (ed.) Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007). pp. 109–112. Martin-Luther-Universität Halle-Wittenberg (2007).The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussing on a formal description and analysis of the resulting “folksonomies�?. An interesting outcome is that the characteristic qualities of these systems seem to be inverse to more traditional knowledge structuring approaches like taxonomies or ontologies: The latter provide rich and precise semantics, but suffer - amongst others - from a knowledge acquisition bottleneck. An important step towards exploiting the possible synergies by bridging the gap between both paradigms is the automatic extraction of relations between tags in a folksonomy. This position paper presents preliminary results of ongoing work to induce hierarchical relationships among tags by analyzing the aggregated data of collaborative tagging systems as a basis for an ontology learning procedure.
@inproceedings{benz2007position,
abstract = {The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussing on a formal description and analysis of the resulting “folksonomies�?. An interesting outcome is that the characteristic qualities of these systems seem to be inverse to more traditional knowledge structuring approaches like taxonomies or ontologies: The latter provide rich and precise semantics, but suffer - amongst others - from a knowledge acquisition bottleneck. An important step towards exploiting the possible synergies by bridging the gap between both paradigms is the automatic extraction of relations between tags in a folksonomy. This position paper presents preliminary results of ongoing work to induce hierarchical relationships among tags by analyzing the aggregated data of collaborative tagging systems as a basis for an ontology learning procedure.},
author = {Benz, Dominik and Hotho, Andreas},
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note = {http://lwa07.informatik.uni-halle.de/kdml07/kdml07.htm},
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%I Martin-Luther-Universität Halle-Wittenberg
%P 109--112
%T Position Paper: Ontology Learning from Folksonomies
%U https://www.kde.cs.uni-kassel.de/pub/pdf/benz2007position.pdf
%X The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussing on a formal description and analysis of the resulting “folksonomies�?. An interesting outcome is that the characteristic qualities of these systems seem to be inverse to more traditional knowledge structuring approaches like taxonomies or ontologies: The latter provide rich and precise semantics, but suffer - amongst others - from a knowledge acquisition bottleneck. An important step towards exploiting the possible synergies by bridging the gap between both paradigms is the automatic extraction of relations between tags in a folksonomy. This position paper presents preliminary results of ongoing work to induce hierarchical relationships among tags by analyzing the aggregated data of collaborative tagging systems as a basis for an ontology learning procedure.
%@ 978-3-86010-907-6 - 1.Jäschke, R., Marinho, L., Hotho, A., Schmidt-Thieme, L., Stumme, G.: Tag Recommendations in Folksonomies. In: Hinneburg, A. (ed.) Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007). pp. 13–20. Martin-Luther-Universität Halle-Wittenberg (2007).Collaborative tagging systems allow users to assign keywords—so called “tags”—to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we present two tag recommendation algorithms: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank, an adaptation of the well-known PageRank algorithm that can cope with undirected triadic hyperedges. We evaluate and compare both algorithms on large-scale real life datasets and show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.
@inproceedings{jaeschke07tagKdml,
abstract = {Collaborative tagging systems allow users to assign keywords—so called “tags”—to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we present two tag recommendation algorithms: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank, an adaptation of the well-known PageRank algorithm that can cope with undirected triadic hyperedges. We evaluate and compare both algorithms on large-scale real life datasets and show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.},
author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
booktitle = {Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)},
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%A Jäschke, Robert
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%E Hinneburg, Alexander
%I Martin-Luther-Universität Halle-Wittenberg
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%T Tag Recommendations in Folksonomies
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%X Collaborative tagging systems allow users to assign keywords—so called “tags”—to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied. In this paper we present two tag recommendation algorithms: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank, an adaptation of the well-known PageRank algorithm that can cope with undirected triadic hyperedges. We evaluate and compare both algorithms on large-scale real life datasets and show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.
%@ 978-3-86010-907-6 - 1.Grahl, M., Hotho, A., Stumme, G.: Conceptual Clustering of Social Bookmark Sites. In: Hinneburg, A. (ed.) Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007). pp. 50–54. Martin-Luther-Universität Halle-Wittenberg (2007).
@inproceedings{grahl07conceptualKdml,
author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
booktitle = {Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)},
editor = {Hinneburg, Alexander},
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}%0 Conference Paper
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%E Hinneburg, Alexander
%I Martin-Luther-Universität Halle-Wittenberg
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%T Conceptual Clustering of Social Bookmark Sites
%U https://www.kde.cs.uni-kassel.de/hotho/pub/2007/kdml_recommender_final.pdf
%@ 978-3-86010-907-6 - 1.Jäschke, R., Hotho, A., Schmitz, C., Stumme, G.: Analysis of the Publication Sharing Behaviour in {BibSonomy}. In: Proceedings of the 15th International Conference on Conceptual Structures. , Sheffield, England (2007).BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
@inproceedings{jaeschke2007analysis,
abstract = {BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.},
address = {Sheffield, England},
author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd},
booktitle = {Proceedings of the 15th International Conference on Conceptual Structures},
keywords = {bibsonomy},
month = {07},
series = {LNCS},
title = {Analysis of the Publication Sharing Behaviour in {BibSonomy}},
volume = 4604,
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}%0 Conference Paper
%1 jaeschke2007analysis
%A Jäschke, Robert
%A Hotho, Andreas
%A Schmitz, Christoph
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%X BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis. - 1.Völker, J., Vrandecic, D., Sure, Y., Hotho, A.: {Learning Disjointness}. In: Franconi, E., Kifer, M., and May, W. (eds.) Proceedings of the European Semantic Web Conference, ESWC2007. Springer-Verlag (2007).
@inproceedings{voelker1:07:eswc,
author = {Völker, Johanna and Vrandecic, Denny and Sure, York and Hotho, Andreas},
booktitle = {Proceedings of the European Semantic Web Conference, ESWC2007},
editor = {Franconi, Enrico and Kifer, Michael and May, Wolfgang},
keywords = {ontology},
month = {07},
publisher = {Springer-Verlag},
series = {Lecture Notes in Computer Science},
title = {{Learning Disjointness}},
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}%0 Conference Paper
%1 voelker1:07:eswc
%A Völker, Johanna
%A Vrandecic, Denny
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%A Hotho, Andreas
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%D 2007
%E Franconi, Enrico
%E Kifer, Michael
%E May, Wolfgang
%I Springer-Verlag
%T {Learning Disjointness}
%U http://www.eswc2007.org/pdf/eswc07-voelker1.pdf
%V 4519 - 1.Schmitz, C., Grahl, M., Hotho, A., Stumme, G., Catutto, C., Baldassarri, A., Loreto, V., Servedio, V.D.P.: Network Properties of Folksonomies. In: Proc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization’’. , Banff (2007).
@inproceedings{schmitz07network,
address = {Banff},
author = {Schmitz, Christoph and Grahl, Miranda and Hotho, Andreas and Stumme, Gerd and Catutto, Ciro and Baldassarri, Andrea and Loreto, Vittorio and Servedio, Vito D. P.},
booktitle = {Proc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization''},
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%1 schmitz07network
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%A Grahl, Miranda
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%A Loreto, Vittorio
%A Servedio, Vito D. P.
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%T Network Properties of Folksonomies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2007/schmitz07network.pdf - 1.Cattuto, C., Schmitz, C., Baldassarri, A., Servedio, V.D.P., Loreto, V., Hotho, A., Grahl, M., Stumme, G.: Network Properties of Folksonomies. AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering’’. 20, 245–262 (2007).
@article{cattuto2007network,
author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd},
editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen},
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}%0 Journal Article
%1 cattuto2007network
%A Cattuto, Ciro
%A Schmitz, Christoph
%A Baldassarri, Andrea
%A Servedio, Vito D. P.
%A Loreto, Vittorio
%A Hotho, Andreas
%A Grahl, Miranda
%A Stumme, Gerd
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%E Hoche, Susanne
%E Nürnberger, Andreas
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%P 245-262
%T Network Properties of Folksonomies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf
%V 20 - 1.Benz, D., Tso, K.H.L., Schmidt-Thieme, L.: Supporting Collaborative Hierarchical Classification: Bookmarks as an Example. Special Issue of the Computer Networks journal on Innovations in Web Communications Infrastructure. 51, 4574–4585 (2007). https://doi.org/http://dx.doi.org/10.1016/j.comnet.2007.06.014.Bookmarks (or favorites, hotlists) are popular strategies to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbor-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. A prototype system called CariBo has been implemented as a plugin for the central bookmark server software SiteBar. All findings have been evaluated on a reasonably large scale, real user dataset with promising results, and possible implications for shared and social bookmarking systems are discussed.
@article{benz2007supporting,
abstract = {Bookmarks (or favorites, hotlists) are popular strategies to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbor-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. A prototype system called CariBo has been implemented as a plugin for the central bookmark server software SiteBar. All findings have been evaluated on a reasonably large scale, real user dataset with promising results, and possible implications for shared and social bookmarking systems are discussed.},
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%V 51
%X Bookmarks (or favorites, hotlists) are popular strategies to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbor-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. A prototype system called CariBo has been implemented as a plugin for the central bookmark server software SiteBar. All findings have been evaluated on a reasonably large scale, real user dataset with promising results, and possible implications for shared and social bookmarking systems are discussed. - 1.Alani, H., Noy, N., Stumme, G., Mika, P., Sure, Y., Vrandecic, D. eds.: Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007. , Banff, Canada (2007).
@proceedings{alani2007workshop,
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editor = {Alani, Harith and Noy, Natasha and Stumme, Gerd and Mika, Peter and Sure, York and Vrandecic, Denny},
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%U http://www2007.org/workshop-W7.php - 1.Hotho, A., Stumme, G.: Mining the World Wide Web --- Methods, Applications, and Perspectives. Künstliche Intelligenz. 5–8 (2007).
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%U http://kobra.bibliothek.uni-kassel.de/bitstream/urn:nbn:de:hebis:34-2008021320337/3/HothoStummeMiningWWW.pdf - 1.Hotho, A., Stumme, G. eds.: Themenheft Web Mining, Künstliche Intelligenz. (2007).
@proceedings{themenheft2007webmining,
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%U http://www.kuenstliche-intelligenz.de/index.php?id=7758 - 1.Chen, L., Cudré-Mauroux, P., Haase, P., Hotho, A., Ong, E. eds.: Proceedings of the First International Workshop on Emergent Semantics and Ontology Evolution, ESOE 2007, co-located with ISWC 2007 + ASWC 2007, Busan, Korea, November 12th, 2007. CEUR-WS.org (2007).
@proceedings{semweb2007esoe,
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%V 292 - 1.Berendt, B., Hotho, A., Mladenic, D., Semeraro, G. eds.: From Web to Social Web: Discovering and Deploying User and Content Profiles. Springer, Berlin, Germany (2007).This book constitutes the refereed proceedings of the Workshop on Web Mining, WebMine 2006, held in Berlin, Germany, September 18th, 2006. Topics included are data mining based on analysis of bloggers and tagging, web mining, XML mining and further techniques of knowledge discovery. The book is especially valuable for those interested in the aspects of the Social Web (Web 2.0) and its inherent dynamic and diversity of user-generated content.
@book{Berendt2007,
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%@ 978-3-540-74950-9 - 1.Jäschke, R., Grahl, M., Hotho, A., Krause, B., Schmitz, C., Stumme, G.: Organizing Publications and Bookmarks in BibSonomy. In: Alani, H., Noy, N., Stumme, G., Mika, P., Sure, Y., and Vrandecic, D. (eds.) Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007. , Banff, Canada (2007).
@inproceedings{jaeschke07organizing,
address = {Banff, Canada},
author = {Jäschke, Robert and Grahl, Miranda and Hotho, Andreas and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
booktitle = {Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007},
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title = {Organizing Publications and Bookmarks in BibSonomy},
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}%0 Conference Paper
%1 jaeschke07organizing
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%A Schmitz, Christoph
%A Stumme, Gerd
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%C Banff, Canada
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%E Alani, Harith
%E Noy, Natasha
%E Stumme, Gerd
%E Mika, Peter
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%E Vrandecic, Denny
%T Organizing Publications and Bookmarks in BibSonomy
%U http://www2007.org/workshops/paper_25.pdf - 1.Eckert, K., Stuckenschmidt, H., Pfeffer, M.: {Interactive Thesaurus Assessment for Automatic Document Annotation}. In: {Proceedings of The Fourth International Conference on Knowledge Capture (K-CAP 2007), Whistler, Canada} (2007).
@inproceedings{eckert2007interactive,
author = {Eckert, Kai and Stuckenschmidt, Heiner and Pfeffer, Magnus},
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%1 eckert2007interactive
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%T {Interactive Thesaurus Assessment for Automatic Document Annotation} - 1.Grahl, M., Hotho, A., Stumme, G.: Conceptual Clustering of Social Bookmarking Sites. In: 7th International Conference on Knowledge Management (I-KNOW ’07). pp. 356–364. Know-Center, Graz, Austria (2007).Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the system, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio.us bookmarking system.
@inproceedings{grahl2007clustering,
abstract = {Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the system, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio.us bookmarking system.},
address = {Graz, Austria},
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2006
- 1.Berendt, B., Hotho, A., Mladenic, D., Semeraro, G. eds.: Workshop on Web Mining 2006 (WebMine). (2006).
@proceedings{berendt2006webmining,
editor = {Berendt, B. and Hotho, A. and Mladenic, D. and Semeraro, G.},
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%U https://www.kde.cs.uni-kassel.de/ws/webmine2006/pdf/WebMine2006.pdf - 1.Schmitz, C., Hotho, A., Jäschke, R., Stumme, G.: Content Aggregation on Knowledge Bases using Graph Clustering. In: Proceedings of the 3rd European Semantic Web Conference. pp. 530–544. Springer, Budva, Montenegro (2006).
@inproceedings{schmitz2006content,
address = {Budva, Montenegro},
author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
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%A Jäschke, Robert
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%I Springer
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%V 4011
%@ 3-540-34544-2 - 1.Jäschke, R., Hotho, A., Schmitz, C., Ganter, B., Stumme, G.: TRIAS - An Algorithm for Mining Iceberg Tri-Lattices. In: Proc. 6th ICDM conference. , Hong Kong (2006).
@inproceedings{trias06jaeschke,
address = {Hong Kong},
author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
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}%0 Conference Paper
%1 trias06jaeschke
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%T TRIAS - An Algorithm for Mining Iceberg Tri-Lattices - 1.Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Emergent Semantics in BibSonomy. In: Hochberger, C. and Liskowsky, R. (eds.) Informatik 2006 - Informatik für Menschen. pp. 305–312. Gesellschaft für Informatik, Bonn (2006).Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.
@inproceedings{hotho2006emergent,
abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.},
address = {Bonn},
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%X Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.
%@ 978-3-88579-188-1 - 1.Schmitz, C., Löser, A.: How to model Semantic Peer-to-Peer Overlays?. In: Proc. P2PIR Workshop, Informatik 2006. , Dresden (2006).
@inproceedings{schmitz2006howto,
address = {Dresden},
author = {Schmitz, Christoph and Löser, Alexander},
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%T How to model Semantic Peer-to-Peer Overlays? - 1.Schmitz, C., Hotho, A., Jäschke, R., Stumme, G.: Mining Association Rules in Folksonomies. In: Proc. IFCS 2006 Conference. , Ljubljana (2006).
@inproceedings{schmitz2006mining,
address = {Ljubljana},
author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
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%T Mining Association Rules in Folksonomies - 1.Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: {BibSonomy}: A Social Bookmark and Publication Sharing System. In: de Moor, A., Polovina, S., and Delugach, H. (eds.) Proceedings of the Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures. Aalborg University Press, Aalborg, Denmark (2006).
@inproceedings{hjss06bibsonomy,
address = {Aalborg, Denmark},
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
booktitle = {Proceedings of the Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures},
editor = {de Moor, Aldo and Polovina, Simon and Delugach, Harry},
keywords = {bookmarking},
month = {07},
publisher = {Aalborg University Press},
title = {{BibSonomy}: A Social Bookmark and Publication Sharing System},
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}%0 Conference Paper
%1 hjss06bibsonomy
%A Hotho, Andreas
%A Jäschke, Robert
%A Schmitz, Christoph
%A Stumme, Gerd
%B Proceedings of the Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures
%C Aalborg, Denmark
%D 2006
%E de Moor, Aldo
%E Polovina, Simon
%E Delugach, Harry
%I Aalborg University Press
%T {BibSonomy}: A Social Bookmark and Publication Sharing System - 1.Schmitz, C., Hotho, A., Jäschke, R., Stumme, G.: Content Aggregation on Knowledge Bases using Graph Clustering. In: Sure, Y. and Domingue, J. (eds.) The Semantic Web: Research and Applications. pp. 530–544. Springer, Berlin/Heidelberg (2006). https://doi.org/10.1007/11762256_39.Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper provides a graph clustering technique on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.
@inproceedings{schmitz2006content,
abstract = {Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper provides a graph clustering technique on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.},
address = {Berlin/Heidelberg},
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%E Domingue, John
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%X Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper provides a graph clustering technique on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.
%@ 978-3-540-34544-2 - 1.Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y. and Domingue, J. (eds.) The Semantic Web: Research and Applications. pp. 411–426. Springer, Berlin/Heidelberg (2006). https://doi.org/10.1007/11762256_31.Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.
@inproceedings{hotho2006information,
abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.},
address = {Berlin/Heidelberg},
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
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}%0 Conference Paper
%1 hotho2006information
%A Hotho, Andreas
%A Jäschke, Robert
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%C Berlin/Heidelberg
%D 2006
%E Sure, York
%E Domingue, John
%I Springer
%P 411--426
%R 10.1007/11762256_31
%T Information Retrieval in Folksonomies: Search and Ranking
%U https://www.kde.cs.uni-kassel.de/hotho/pub/2006/seach2006hotho_eswc.pdf
%V 4011
%X Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. - 1.Hoser, B., Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Semantic Network Analysis of Ontologies. In: Sure, Y. and Domingue, J. (eds.) The Semantic Web: Research and Applications. pp. 514–529. Springer, Heidelberg (2006).A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.
@inproceedings{hoser2006semantic,
abstract = {A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.},
address = {Heidelberg},
author = {Hoser, Bettina and Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
booktitle = {The Semantic Web: Research and Applications},
editor = {Sure, York and Domingue, John},
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pages = {514-529},
publisher = {Springer},
series = {LNAI},
title = {Semantic Network Analysis of Ontologies},
volume = 4011,
year = 2006
}%0 Conference Paper
%1 hoser2006semantic
%A Hoser, Bettina
%A Hotho, Andreas
%A Jäschke, Robert
%A Schmitz, Christoph
%A Stumme, Gerd
%B The Semantic Web: Research and Applications
%C Heidelberg
%D 2006
%E Sure, York
%E Domingue, John
%I Springer
%P 514-529
%T Semantic Network Analysis of Ontologies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2006/hoser2006semantic.pdf
%V 4011
%X A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size. - 1.Jäschke, R., Hotho, A., Schmitz, C., Stumme, G.: Wege zur Entdeckung von Communities in Folksonomies. In: Braß, S. and Hinneburg, A. (eds.) Proc. 18. Workshop Grundlagen von Datenbanken. pp. 80–84. Martin-Luther-Universität, Halle-Wittenberg (2006).Ein wichtiger Baustein des neu entdeckten World Wide Web -- des "`Web 2.0"' -- stellen Folksonomies dar. In diesen Systemen können Benutzer gemeinsam Ressourcen verwalten und mit Schlagwörtern versehen. Die dadurch entstehenden begrifflichen Strukturen stellen ein interessantes Forschungsfeld dar. Dieser Artikel untersucht Ansätze und Wege zur Entdeckung und Strukturierung von Nutzergruppen ("Communities") in Folksonomies.
@inproceedings{jaeschke2006wege,
abstract = {Ein wichtiger Baustein des neu entdeckten World Wide Web -- des "`Web 2.0"' -- stellen Folksonomies dar. In diesen Systemen können Benutzer gemeinsam Ressourcen verwalten und mit Schlagwörtern versehen. Die dadurch entstehenden begrifflichen Strukturen stellen ein interessantes Forschungsfeld dar. Dieser Artikel untersucht Ansätze und Wege zur Entdeckung und Strukturierung von Nutzergruppen ("Communities") in Folksonomies.},
address = {Halle-Wittenberg},
author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd},
booktitle = {Proc. 18. Workshop Grundlagen von Datenbanken},
editor = {Braß, Stefan and Hinneburg, Alexander},
keywords = {itegpub},
month = {06},
pages = {80-84},
publisher = {Martin-Luther-Universität},
title = {Wege zur Entdeckung von Communities in Folksonomies},
year = 2006
}%0 Conference Paper
%1 jaeschke2006wege
%A Jäschke, Robert
%A Hotho, Andreas
%A Schmitz, Christoph
%A Stumme, Gerd
%B Proc. 18. Workshop Grundlagen von Datenbanken
%C Halle-Wittenberg
%D 2006
%E Braß, Stefan
%E Hinneburg, Alexander
%I Martin-Luther-Universität
%P 80-84
%T Wege zur Entdeckung von Communities in Folksonomies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2006/jaeschke2006wege.pdf
%X Ein wichtiger Baustein des neu entdeckten World Wide Web -- des "`Web 2.0"' -- stellen Folksonomies dar. In diesen Systemen können Benutzer gemeinsam Ressourcen verwalten und mit Schlagwörtern versehen. Die dadurch entstehenden begrifflichen Strukturen stellen ein interessantes Forschungsfeld dar. Dieser Artikel untersucht Ansätze und Wege zur Entdeckung und Strukturierung von Nutzergruppen ("Communities") in Folksonomies. - 1.Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Trend Detection in Folksonomies. In: Avrithis, Y.S., Kompatsiaris, Y., Staab, S., and O’Connor, N.E. (eds.) Proc. First International Conference on Semantics And Digital Media Technology (SAMT). pp. 56–70. Springer, Heidelberg (2006).As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.
@inproceedings{hotho2006trend,
abstract = {As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.},
address = {Heidelberg},
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
booktitle = {Proc. First International Conference on Semantics And Digital Media Technology (SAMT)},
editor = {Avrithis, Yannis S. and Kompatsiaris, Yiannis and Staab, Steffen and O'Connor, Noel E.},
keywords = {folksonomy},
month = 12,
pages = {56-70},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
title = {Trend Detection in Folksonomies},
volume = 4306,
year = 2006
}%0 Conference Paper
%1 hotho2006trend
%A Hotho, Andreas
%A Jäschke, Robert
%A Schmitz, Christoph
%A Stumme, Gerd
%B Proc. First International Conference on Semantics And Digital Media Technology (SAMT)
%C Heidelberg
%D 2006
%E Avrithis, Yannis S.
%E Kompatsiaris, Yiannis
%E Staab, Steffen
%E O'Connor, Noel E.
%I Springer
%P 56-70
%T Trend Detection in Folksonomies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf
%V 4306
%X As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.
%@ 3-540-49335-2 - 1.Alani, H., Hoser, B., Schmitz, C., Stumme, G. eds.: Proceedings of the 2nd Workshop on Semantic Network Analysis. (2006).
@proceedings{alani2006proceedings,
editor = {Alani, Harith and Hoser, Bettina and Schmitz, Christoph and Stumme, Gerd},
keywords = {workshop},
title = {Proceedings of the 2nd Workshop on Semantic Network Analysis},
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}%0 Conference Proceedings
%1 alani2006proceedings
%D 2006
%E Alani, Harith
%E Hoser, Bettina
%E Schmitz, Christoph
%E Stumme, Gerd
%T Proceedings of the 2nd Workshop on Semantic Network Analysis
%U https://www.kde.cs.uni-kassel.de/ws/sna2006/ - 1.Bloehdorn, S., Cimiano, P., Hotho, A.: Learning Ontologies to Improve Text Clustering and Classification. In: From Data and Information Analysis to Knowledge Engineering. pp. 334–341. Springer Berlin Heidelberg (2006). https://doi.org/http://dx.doi.org/10.1007/3-540-31314-1_40.Recent work has shown improvements in text clustering and classification tasks by integrating conceptual features extracted from ontologies. In this paper we present text mining experiments in the medical domain in which the ontological structures used are acquired automatically in an unsupervised learning process from the text corpus in question. We compare results obtained using the automatically learned ontologies with those obtained using manually engineered ones. Our results show that both types of ontologies improve results on text clustering and classification tasks, whereby the automatically acquired ontologies yield a improvement competitive with the manually engineered ones. ER -
@incollection{bloehdorn2006learning,
abstract = {Recent work has shown improvements in text clustering and classification tasks by integrating conceptual features extracted from ontologies. In this paper we present text mining experiments in the medical domain in which the ontological structures used are acquired automatically in an unsupervised learning process from the text corpus in question. We compare results obtained using the automatically learned ontologies with those obtained using manually engineered ones. Our results show that both types of ontologies improve results on text clustering and classification tasks, whereby the automatically acquired ontologies yield a improvement competitive with the manually engineered ones. ER -},
author = {Bloehdorn, Stephan and Cimiano, Philipp and Hotho, Andreas},
booktitle = {From Data and Information Analysis to Knowledge Engineering},
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%1 bloehdorn2006learning
%A Bloehdorn, Stephan
%A Cimiano, Philipp
%A Hotho, Andreas
%B From Data and Information Analysis to Knowledge Engineering
%D 2006
%I Springer Berlin Heidelberg
%P 334--341
%R http://dx.doi.org/10.1007/3-540-31314-1_40
%T Learning Ontologies to Improve Text Clustering and Classification
%U https://www.kde.cs.uni-kassel.de/hotho/pub/2006/2006-03-gfkl05-bloehdorn-etal-learning-ontologies.pdf
%X Recent work has shown improvements in text clustering and classification tasks by integrating conceptual features extracted from ontologies. In this paper we present text mining experiments in the medical domain in which the ontological structures used are acquired automatically in an unsupervised learning process from the text corpus in question. We compare results obtained using the automatically learned ontologies with those obtained using manually engineered ones. Our results show that both types of ontologies improve results on text clustering and classification tasks, whereby the automatically acquired ontologies yield a improvement competitive with the manually engineered ones. ER -
%@ 978-3-540-31313-7 - 1.Benz, D., Tso, K.H.L., Schmidt-Thieme, L.: Automatic Bookmark Classification - A Collaborative Approach. In: Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006. , Edinburgh, Scotland (2006).Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.
@inproceedings{benz2006automatic,
abstract = {Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.},
address = {Edinburgh, Scotland},
author = {Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars},
booktitle = {Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006},
keywords = {itegpub},
month = {05},
note = {isbn = {085432853X}},
title = {Automatic Bookmark Classification - A Collaborative Approach},
year = 2006
}%0 Conference Paper
%1 benz2006automatic
%A Benz, Dominik
%A Tso, Karen H. L.
%A Schmidt-Thieme, Lars
%B Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006
%C Edinburgh, Scotland
%D 2006
%T Automatic Bookmark Classification - A Collaborative Approach
%U https://www.kde.cs.uni-kassel.de/pub/pdf/benz2006automatic.pdf
%X Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach. - 1.Stumme, G., Hotho, A., Berendt, B.: Semantic Web Mining - State of the Art and Future Directions. Journal of Web Semantics. 4, 124–143 (2006).SemanticWeb Mining aims at combining the two fast-developing research areas SemanticWeb andWeb Mining. This survey analyzes the convergence of trends from both areas: an increasing number of researchers is working on improving the results ofWeb Mining by exploiting semantic structures in theWeb, and they make use ofWeb Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.
@article{jws2006Semantic,
abstract = {SemanticWeb Mining aims at combining the two fast-developing research areas SemanticWeb andWeb Mining. This survey analyzes the convergence of trends from both areas: an increasing number of researchers is working on improving the results ofWeb Mining by exploiting semantic structures in theWeb, and they make use ofWeb Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.},
author = {Stumme, Gerd and Hotho, Andreas and Berendt, Bettina},
journal = {Journal of Web Semantics},
keywords = {sota},
number = 2,
pages = {124-143},
publisher = {Elsevier},
title = {Semantic Web Mining - State of the Art and Future Directions},
volume = 4,
year = 2006
}%0 Journal Article
%1 jws2006Semantic
%A Stumme, Gerd
%A Hotho, Andreas
%A Berendt, Bettina
%D 2006
%I Elsevier
%J Journal of Web Semantics
%N 2
%P 124-143
%T Semantic Web Mining - State of the Art and Future Directions
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2006/stumme2006semantic.pdf
%V 4
%X SemanticWeb Mining aims at combining the two fast-developing research areas SemanticWeb andWeb Mining. This survey analyzes the convergence of trends from both areas: an increasing number of researchers is working on improving the results ofWeb Mining by exploiting semantic structures in theWeb, and they make use ofWeb Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable. - 1.Bloehdorn, S., Hotho, A.: Boosting for Text Classification with Semantic Features. (2006). https://doi.org/10.1007/11899402_10.
@book{citeulike:910161,
author = {Bloehdorn, Stephan and Hotho, Andreas},
journal = {Lecture Notes in Computer Science : Advances in Web Mining and Web Usage Analysis},
keywords = {classification},
pages = {149--166},
title = {Boosting for Text Classification with Semantic Features},
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%R 10.1007/11899402_10
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%@ 978-3-540-47127-1 - 1.Ackermann, M., Berendt, B., Grobelnik, M., Hotho, A., Mladenic, D., Semeraro, G., Spiliopoulou, M., Stumme, G., Svatek, V., van Someren, M. eds.: Semantics, Web and Mining. Springer, Heidelberg (2006).
@book{Semantic2006Ackermann,
address = {Heidelberg},
editor = {Ackermann, Markus and Berendt, Bettina and Grobelnik, Marko and Hotho, Andreas and Mladenic, Dunja and Semeraro, Giovanni and Spiliopoulou, Myra and Stumme, Gerd and Svatek, Vojtech and van Someren, Maarten},
keywords = {itegpub},
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title = {Semantics, Web and Mining},
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%1 Semantic2006Ackermann
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%E Berendt, Bettina
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%E Hotho, Andreas
%E Mladenic, Dunja
%E Semeraro, Giovanni
%E Spiliopoulou, Myra
%E Stumme, Gerd
%E Svatek, Vojtech
%E van Someren, Maarten
%I Springer
%T Semantics, Web and Mining
%U http://dx.doi.org/10.1007/11908678 - 1.Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: FolkRank: A Ranking Algorithm for Folksonomies. In: Proc. FGIR 2006 (2006).In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006.
@inproceedings{hotho2006folkrank,
abstract = {In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006.},
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
booktitle = {Proc. FGIR 2006},
keywords = {itegpub},
title = {FolkRank: A Ranking Algorithm for Folksonomies},
year = 2006
}%0 Conference Paper
%1 hotho2006folkrank
%A Hotho, Andreas
%A Jäschke, Robert
%A Schmitz, Christoph
%A Stumme, Gerd
%B Proc. FGIR 2006
%D 2006
%T FolkRank: A Ranking Algorithm for Folksonomies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf
%X In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006. - 1.Macek, K.H.N.B.-E.: Äquivalenzbetrachtungen zu den Klassen N und NC, (2006).Die vorliegende Studienarbeit beschäftigt sich mit dem Artikel "Separating NC along the \delta axis" von Bellantoni und Oitavem (ENTCS 2003). Darin wird ein Termsystem N* über Binärbäumen mit Blattspeicherung, angereichert um Konstanten für Baumrekursion, vorgestellt und im Stile Bellantoni/Niggl ein Maß \rho auf N* erklärt. Das System N besteht dann aus genau den geschlossenen N*-Termen mit \rho-Maß kleiner order gleich 1. Nach sorgfältiger Ausarbeitung der in der Arbeit dargestellten Ideen und Konstruktionen für den Beweis der Vollständigkeit des Systems N, daß nämlich jede NC-Funktion in System N definiert (berechnet) werden kann, kommt diese Studienarbeit zu dem Schluß, daß Vollständigkeit als zentrale Inklusion in der Charakterisierung von NC durch N so wie vorgestellt nicht gehalten werden kann.
@misc{macek2006quivalenzbetrachtungen,
abstract = {Die vorliegende Studienarbeit beschäftigt sich mit dem Artikel "Separating NC along the \delta axis" von Bellantoni und Oitavem (ENTCS 2003). Darin wird ein Termsystem N* über Binärbäumen mit Blattspeicherung, angereichert um Konstanten für Baumrekursion, vorgestellt und im Stile Bellantoni/Niggl ein Maß \rho auf N* erklärt. Das System N besteht dann aus genau den geschlossenen N*-Termen mit \rho-Maß kleiner order gleich 1. Nach sorgfältiger Ausarbeitung der in der Arbeit dargestellten Ideen und Konstruktionen für den Beweis der Vollständigkeit des Systems N, daß nämlich jede NC-Funktion in System N definiert (berechnet) werden kann, kommt diese Studienarbeit zu dem Schluß, daß Vollständigkeit als zentrale Inklusion in der Charakterisierung von NC durch N so wie vorgestellt nicht gehalten werden kann.},
author = {Macek, Karl Heinz Niggl Björn-Elmar},
keywords = {Recursion},
title = {Äquivalenzbetrachtungen zu den Klassen N und NC},
year = 2006
}%0 Generic
%1 macek2006quivalenzbetrachtungen
%A Macek, Karl Heinz Niggl Björn-Elmar
%D 2006
%T Äquivalenzbetrachtungen zu den Klassen N und NC
%X Die vorliegende Studienarbeit beschäftigt sich mit dem Artikel "Separating NC along the \delta axis" von Bellantoni und Oitavem (ENTCS 2003). Darin wird ein Termsystem N* über Binärbäumen mit Blattspeicherung, angereichert um Konstanten für Baumrekursion, vorgestellt und im Stile Bellantoni/Niggl ein Maß \rho auf N* erklärt. Das System N besteht dann aus genau den geschlossenen N*-Termen mit \rho-Maß kleiner order gleich 1. Nach sorgfältiger Ausarbeitung der in der Arbeit dargestellten Ideen und Konstruktionen für den Beweis der Vollständigkeit des Systems N, daß nämlich jede NC-Funktion in System N definiert (berechnet) werden kann, kommt diese Studienarbeit zu dem Schluß, daß Vollständigkeit als zentrale Inklusion in der Charakterisierung von NC durch N so wie vorgestellt nicht gehalten werden kann. - 1.Haase, P., Ehrig, M., Hotho, A., Schnizler, B.: Personalized Information Access in a Bibliographic Peer-to-Peer System. In: Staab, S. and Stuckenschmidt, H. (eds.) Peer-to-Peer and SemanticWeb, Decentralized Management and Exchange of Knowledge and Information. pp. 143–158. Springer (2006).
@incollection{Haase04Personalized,
author = {Haase, Peter and Ehrig, Marc and Hotho, Andreas and Schnizler, Björn},
booktitle = {Peer-to-Peer and SemanticWeb, Decentralized Management and Exchange of Knowledge and Information},
editor = {Staab, Steffen and Stuckenschmidt, Heiner},
keywords = {ontology},
pages = {143--158},
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%A Ehrig, Marc
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%E Staab, Steffen
%E Stuckenschmidt, Heiner
%I Springer
%P 143--158
%T Personalized Information Access in a Bibliographic Peer-to-Peer System
%@ 3-540-28346-3 - 1.Schmitz, C., Hotho, A., Jäschke, R., Stumme, G.: Kollaboratives Wissensmanagement. In: Pellegrini, T. and Blumauer, A. (eds.) Semantic Web - Wege zur vernetzten Wissensgesellschaft. pp. 273–290. Springer (2006).Wissensmanagement in zentralisierten Wissensbasen erfordert einen hohen Aufwand für Erstellung und Wartung, und es entspricht nicht immer den Anforderungen der Benutzer. Wir geben in diesem Kapitel einen Überblick über zwei aktuelle Ansätze, die durch kollaboratives Wissensmanagement diese Probleme lösen können. Im Peer-to-Peer-Wissensmanagement unterhalten Benutzer dezentrale Wissensbasen, die dann vernetzt werden können, um andere Benutzer eigene Inhalte nutzen zu lassen. Folksonomies versprechen, die Wissensakquisition so einfach wie möglich zu gestalten und so viele Benutzer in den Aufbau und die Pflege einer gemeinsamen Wissensbasis einzubeziehen.
@inbook{schmitz2006kollaboratives,
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%@ 3-540-29324-8 - 1.Hotho, A., J�schke, R., Schmitz, C., Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y. and Domingue, J. (eds.) The Semantic Web: Research and Applications. pp. 411–426. Springer, Heidelberg (2006).
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2005
- 1.Hotho, A.: Text Clustern mit Hintergrundwissen (Dissertationsbeschreibung). Künstliche Intelligenz (KI). 1, 62–64 (2005).
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%V 1 - 1.Haase, P., Schmitz, C., Sure, Y. eds.: Ontologies in Peer-to-Peer Communities. , Heraklion, Greece (2005).
@proceedings{haase2005ontologies,
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%U https://www.kde.cs.uni-kassel.de/ws/ontop2p2005 - 1.Jäschke, R.: Die Struktur der Monoide binärer Relationen auf endlichen Mengen, https://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2005struktur.pdf, (2005).
@mastersthesis{jaeschke2005struktur,
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%U https://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2005struktur.pdf - 1.Schmitz, C.: Towards Self-Organizing Communities in Peer-to-Peer Knowledge Management. In: Proc. ESWC 2005 Workshop on Ontologies in Peer-to-Peer Communities. , Heraklion, Greece (2005).
@inproceedings{schmitz2005towards,
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%U https://www.kde.cs.uni-kassel.de/schmitz/publ/ontop2p.pdf - 1.Hotho, A., Nürnberger, A., Paaß, G.: A Brief Survey of Text Mining. LDV Forum - GLDV Journal for Computational Linguistics and Language Technology. 20, 19–62 (2005).
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%V 20 - 1.Schmitz, C.: Towards Content Aggregation on Knowledge Bases through Graph Clustering. In: Braß, S. and Goldberg, C. (eds.) Proc. 17. GI-Workshop ``Grundlagen von Datenbanken’’. , Wörlitz (2005).
@inproceedings{schmitz2005towards,
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%U https://www.kde.cs.uni-kassel.de/schmitz/publ/gvd2005_schmitz.pdf - 1.Stumme, G., Hoser, B., Schmitz, C., Alani, H. eds.: ISWC 2005 Workshop on Semantic Network Analysis. , Galway, Ireland (2005).
@proceedings{stumme2005iswc,
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%V 171 - 1.Bloehdorn, S., Cimiano, P., Hotho, A., Staab, S.: An Ontology-based Framework for Text Mining. LDV Forum - GLDV Journal for Computational Linguistics and Language Technology. 20, 87–112 (2005).
@article{bloehdorn-etal-ldv-2005,
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%V 20 - 1.Bloehdorn, S., Buntine, W., Hotho, A. eds.: Proceedings of the Workshop on Learning in Web Search (LWS 2005). (2005).
@proceedings{2005-lws-proceedings,
editor = {Bloehdorn, Stephan and Buntine, Wray and Hotho, Andreas},
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note = {Workshop at the 22nd International Conference on Machine Learning (ICML 2005)},
title = {Proceedings of the Workshop on Learning in Web Search (LWS 2005)},
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%U http://cosco.hiit.fi/search/learninginsearch05/ICML_W4.pdf - 1.Stefani, S.: Rechtliche Aspekte und Implementierung eines Benachrichtigungssystems für Nutzer von Bibliotheken, http://www.svenstefani.de/publ/diplom1/sven_stefani_buecherwecker_unik_diplomarbeit_2005.pdf, (2005).
@mastersthesis{uniksdiplom1,
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%U http://www.svenstefani.de/publ/diplom1/sven_stefani_buecherwecker_unik_diplomarbeit_2005.pdf - 1.Ganter, B., Stumme, G., Wille, R. eds.: Formal Concept Analysis: Foundations and Applications. Springer (2005).
@book{noauthororeditor,
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%T Formal Concept Analysis: Foundations and Applications - 1.Dau, F., Mugnier, M.-L., Stumme, G. eds.: Conceptual Structures: Common Semantics for Sharing Knowledge, 13th International Conference on Conceptual Structures, ICCS 2005, Kassel, Germany, July 17-22, 2005, Proceedings. Springer (2005).
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%@ 3-540-27783-8 - 1.Stumme, G.: Ontology Merging with Formal Concept Analysis. In: Kalfoglou, Y., Schorlemmer, W.M., Sheth, A.P., Staab, S., and Uschold, M. (eds.) Semantic Interoperability and Integration. IBFI, Schloss Dagstuhl, Germany (2005).
@inproceedings{conf/dagstuhl/Stumme05,
author = {Stumme, Gerd},
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editor = {Kalfoglou, Yannis and Schorlemmer, W. Marco and Sheth, Amit P. and Staab, Steffen and Uschold, Michael},
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%V 04391 - 1.Berendt, B., Hotho, A., Stumme, G.: Semantic Web Mining and the Representation, Analysis, and Evolution of Web Space. In: Svatek, V. and Snasel, V. (eds.) Proc. of the 1st Intl. Workshop on Representation and Analysis of Web Space. pp. 1–16. Technical University of Ostrava (2005).
@inproceedings{berendt05semantic,
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%@ 80-248-0864-1 - 1.Stumme, G.: A Finite State Model for On-Line Analytical Processing in Triadic Contexts. In: Ganter, B. and Godin, R. (eds.) Proc. 3rd Intl. Conf. on Formal Concept Analysis. pp. 315–328. Springer, Heidelberg (2005).
@inproceedings{stumme05finite,
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%@ 3-540-24525-1 - 1.Haase, P., Hotho, A., Schmidt-Thieme, L., Sure, Y.: Collaborative and Usage-Driven Evolution of Personal Ontologies. In: G{ó}mez-P{é}rez, A. and Euzenat, J. (eds.) ESWC. pp. 486–499. Springer (2005).
@inproceedings{DBLP:conf/esws/HaaseHSS05,
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%@ 3-540-26124-9 - 1.Berendt, B., Hotho, A., Mladenic, D., Semerano, G., Spiliopoulou, M., Stumme, G., van Someren, M. eds.: Proc. of the European Web Mining Forum 2005. (2005).
@proceedings{berendt05european,
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%U https://www.kde.cs.uni-kassel.de/ws/ewmf05 - 1.Stumme, G., Hoser, B., Schmitz, C., Alani, H. eds.: Proceedings of the First Workshop on Semantic Network Analysis. CEUR Proceedings, Aachen (2005).
@proceedings{stumme05semanticnetworkanalysis,
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%U http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-171/ - 1.Hitzler, P., Lutz, C., Stumme, G. eds.: Foundational Aspects of Ontologies. Universität Koblenz-Landau (2005).
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%V 9-2005 - 1.Lakhal, L., Stumme, G.: Efficient Mining of Association Rules Based on Formal Concept Analysis. In: Ganter, B., Stumme, G., and Wille, R. (eds.) Formal Concept Analysis: Foundations and Applications. pp. 180–195. Springer, Heidelberg (2005).Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, \titanic, and show how FCA helps in reducing the number of resulting rules without loss of information, before giving a general overview over the history and state of the art of applying FCA for association rule mining.
@inbook{lakhal2005efficient,
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%X Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, \titanic, and show how FCA helps in reducing the number of resulting rules without loss of information, before giving a general overview over the history and state of the art of applying FCA for association rule mining. - 1.Pasquier, N., Taouil, R., Bastide, Y., Stumme, G., Lakhal, L.: Generating a Condensed Representation for Association Rules. Journal Intelligent Information Systems (JIIS). 24, 29–60 (2005).
@article{pasquier2005generating,
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%T Generating a Condensed Representation for Association Rules
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf
%V 24 - 1.Stumme, G.: Conceptual Knowledge Processing (Invited Talk). In: Collard, M. and Cavarero, J.-L. (eds.) Ontologies-based techniques for DataBases and Information Systems. p. 5. , Trondheim (2005).
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%U https://www.kde.cs.uni-kassel.de/stumme/papers/2005/stumme2005some_slides.pdf - 1.Dau, F., Mugnier, M.-L., Stumme, G. eds.: Contributions to ICCS 2005. kassel university press, Kassel (2005).
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%@ 3-89958-138-5 - 1.Cimiano, P., Hotho, A., Staab, S.: Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis. Journal on Artificial Intelligence Research. 24, 305–339 (2005).
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2004
- 1.Nejdl, W., Wolpers, M., Siberski, W., Schmitz, C., Schlosser, M., Brunkhorst, I., Löser, A.: Super-Peer-Based Routing Strategies for {RDF}-Based Peer-to-Peer Networks. Journal of Web Semantics. Special issue WWW 2003, (2004).
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%V Special issue WWW 2003 - 1.Mobasher, B., Anand, S.S., Berendt, B., Hotho, A. eds.: Semantic Web Personalization. (2004).
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%T Semantic Web Personalization - 1.Schmitz, C., Staab, S., Tempich, C.: Socialisation in Peer-to-Peer Knowledge Management. In: Proc. International Conference on Knowledge Management (I-Know 2004). , Graz, Austria (2004).
@inproceedings{schmitz2004socialisation,
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%U https://www.kde.cs.uni-kassel.de/schmitz/publ/socialisation.pdf - 1.Haase, P., Ehrig, M., Hotho, A., Schnizler, B.: Personalized Information Access in a Bibliographic Peer-to-Peer System. In: Proceedings of the AAAI Workshop on Semantic Web Personalization, 2004. pp. 1–12. AAAI Press (2004).
@inproceedings{haase04personalized,
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%U https://www.kde.cs.uni-kassel.de/hotho/pub/2004/haase04person.pdf - 1.Schmitz, C.: Self-Organization of a Small World by Topic. In: Proc. 1st International Workshop on Peer-to-Peer Knowledge Management. , Boston, MA (2004).
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%U https://www.kde.cs.uni-kassel.de/schmitz/publ/p2pkm.pdf - 1.Bloehdorn, S., Hotho, A.: Boosting for Text Classification with Semantic Features. In: Proceedings of the MSW 2004 workshop at the 10th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. pp. 70–87 (2004).
@inproceedings{bloehdorn04msw,
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%U https://www.kde.cs.uni-kassel.de/hotho/pub/2004/msw04bloehdorn.pdf - 1.Cimiano, P., Hotho, A., Staab, S.: Clustering Ontologies from Text. In: Proceedings of the Conference on Languages Resources and Evaluation (LREC). ELRA - European Language Ressources Association, Lisbon, Portugal (2004).
@inproceedings{cim04a,
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author = {Cimiano, Philipp and Hotho, Andreas and Staab, Steffen},
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%U https://www.kde.cs.uni-kassel.de/hotho/pub/2004/lrec04.pdf - 1.Ehrig, M., Hartmann, J., Schmitz, C.: {O}ntologie-basiertes {W}eb {M}ining. In: Workshop ``Semantische Technologien für Informationsportale’’ (GI-Jahrestagung 2004). Gesellschaft für Informatik (2004).
@inproceedings{ehrig2004ontologie,
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%U https://www.kde.cs.uni-kassel.de/schmitz/publ/2004-gi-crawler_v3.0.pdf - 1.Bloehdorn, S., Hotho, A.: Boosting for Text Classification with Semantic Features (reprint). In: Proceedings of the Workshop on Text-based Information Retrieval (TIR-04) at the 27th German Conference on Artificial Intelligence (2004).
@inproceedings{bloehdorn04Boosting,
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%U https://www.kde.cs.uni-kassel.de/hotho/pub/2004/tir04final.pdf - 1.Cimiano, P., Hotho, A., Staab, S.: Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis. Institute AIFB, Universität Karlsruhe (2004).
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%U https://www.kde.cs.uni-kassel.de/hotho/pub/2004/icdm04boosting.pdf - 1.Tane, J., Schmitz, C., Stumme, G.: Semantic Resource Management for the Web: An ELearning Application. In: Proc. 13th International World Wide Web Conference (WWW 2004). , New York (2004).
@inproceedings{tane2004semantic,
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%U https://www.kde.cs.uni-kassel.de/schmitz/publ/cwwww04.pdf - 1.Hotho, A., Sure, Y., Getoor, L.: A workshop report: mining for and from the Semantic Web at KDD 2004. SIGKDD Explorations. 6, 142–143 (2004).
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%@ 3-540-23258-3 - 1.Hotho, A.: Clustern mit Hintergrundwissen, (2004).
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%T Clustern mit Hintergrundwissen - 1.Schmidt-Thieme, L., Stumme, G., Rusnak, U., Eberhart, A. eds.: Semantische Technologien für Informationsportale. Gesellschaft für Informatik, Bonn (2004).
@proceedings{schmidt2004semantische,
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%V 51 - 1.Cimiano, P., Hotho, A., Stumme, G., Tane, J.: Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies. In: Eklund, P. (ed.) Concept Lattices. pp. 189–207. Springer, Berlin/Heidelberg (2004).
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%@ 978-3-540-21043-6 - 1.Berendt, B., Hotho, A., Stumme, G.: Usage Mining for and on the Semantic Web. In: Kargupta, H., Joshi, A., Sivakumar, K., and Yesha, Y. (eds.) Data Mining Next Generation Challenges and Future Directions. pp. 461–481. AAAI Press, Boston (2004).
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%@ 0-262-61203-8 - 1.Berendt, B., Hotho, A., Mladenic, D., van Someren, M., Spiliopoulou, M., Stumme, G. eds.: Web Mining: From Web to Semantic Web. Springer, Heidelberg (2004).
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%U https://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt2004roadmap.pdf
%V 3209
%X The purpose of Web mining is to develop methods and systems for discovering models of objects and processes on the World Wide Web and for web-based systems that show adaptive performance. Web Mining integrates three parent areas: Data Mining (we use this term here also for the closely related areas of Machine Learning and Knowledge Discovery), Internet technology and World Wide Web, and for the more recent Semantic Web. The World Wide Web has made an enormous amount of information electronically accessible. The use of email, news and markup languages like HTML allow users to publish and read documents at a world-wide scale and to communicate via chat connections, including information in the form of images and voice records. The HTTP protocol that enables access to documents over the network via Web browsers created an immense improvement in communication and access to information. For some years these possibilities were used mostly in the scientific world but recent years have seen an immense growth in popularity, supported by the wide availability of computers and broadband communication. The use of the internet for other tasks than finding information and direct communication is increasing, as can be seen from the interest in ldquoe-activitiesrdquo such as e-commerce, e-learning, e-government, e-science. - 1.Stumme, G.: Iceberg Query Lattices for Datalog. In: Wolff, K.E., Pfeiffer, H.D., and Delugach, H.S. (eds.) Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004). pp. 109–125. Springer, Heidelberg (2004).
@inproceedings{stumme2004iceberg,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004)},
editor = {Wolff, Karl Erich and Pfeiffer, Heather D. and Delugach, Harry S.},
keywords = {lattices},
pages = {109-125},
publisher = {Springer},
series = {LNCS},
title = {Iceberg Query Lattices for Datalog},
volume = 3127,
year = 2004
}%0 Conference Paper
%1 stumme2004iceberg
%A Stumme, Gerd
%B Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004)
%C Heidelberg
%D 2004
%E Wolff, Karl Erich
%E Pfeiffer, Heather D.
%E Delugach, Harry S.
%I Springer
%P 109-125
%T Iceberg Query Lattices for Datalog
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2004/stumme2004iceberg.pdf
%V 3127 - 1.Cimiano, P., Hotho, A., Staab, S.: Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text. In: de M{á}ntaras, R.L. and Saitta, L. (eds.) Proceedings of the European Conference on Artificial Intelligence (ECAI’04). pp. 435–439. IOS Press, Valencia, Spain (2004).
@inproceedings{cim04c,
address = {Valencia, Spain},
author = {Cimiano, Philipp and Hotho, Andreas and Staab, Steffen},
booktitle = {Proceedings of the European Conference on Artificial Intelligence (ECAI'04)},
editor = {de M{á}ntaras, Ramon L{ó}pez and Saitta, Lorenza},
keywords = {learning},
pages = {435-439},
publisher = {IOS Press},
title = {Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text},
year = 2004
}%0 Conference Paper
%1 cim04c
%A Cimiano, Philipp
%A Hotho, Andreas
%A Staab, Steffen
%B Proceedings of the European Conference on Artificial Intelligence (ECAI'04)
%C Valencia, Spain
%D 2004
%E de M{á}ntaras, Ramon L{ó}pez
%E Saitta, Lorenza
%I IOS Press
%P 435-439
%T Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text
%U https://www.kde.cs.uni-kassel.de/hotho/pub/2004/ecai04.pdf
%@ 1-58603-452-9 - 1.Maedche, A., Sattler, K.-U., Stumme, G. eds.: Information Integration and Mining in Databases and on the Web. Proceedings of the 2nd International Workshop on Databases, Documents, and Information Fusion (DBFusion 2002). , Aachen (2004).
@proceedings{maedche02information,
address = {Aachen},
editor = {Maedche, Alexander and Sattler, Kai-Uwe and Stumme, Gerd},
journal = {CEUR-WS},
keywords = {integration},
series = {CEUR Workshop Proceedings},
title = {Information Integration and Mining in Databases and on the Web. Proceedings of the 2nd International Workshop on Databases, Documents, and Information Fusion (DBFusion 2002)},
volume = 124,
year = 2004
}%0 Conference Proceedings
%1 maedche02information
%B CEUR Workshop Proceedings
%C Aachen
%D 2004
%E Maedche, Alexander
%E Sattler, Kai-Uwe
%E Stumme, Gerd
%J CEUR-WS
%T Information Integration and Mining in Databases and on the Web. Proceedings of the 2nd International Workshop on Databases, Documents, and Information Fusion (DBFusion 2002)
%U http://ftp.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-124/
%V 124 - 1.Hotho, A., Sure, Y., Getoor, L. eds.: International Workshop on Mining for and from the Semantic Web (MSW2004). (2004).
@proceedings{msw2004,
editor = {Hotho, Andreas and Sure, York and Getoor, Lise},
keywords = {workshop},
month = {08},
note = {located at the 10th International ACM SIGKDD Conference on Knowledge Discovery and Data Mining KDD 2004, 22nd August 2004, Seattle, WA, USA},
title = {International Workshop on Mining for and from the Semantic Web (MSW2004)},
year = 2004
}%0 Conference Proceedings
%1 msw2004
%D 2004
%E Hotho, Andreas
%E Sure, York
%E Getoor, Lise
%T International Workshop on Mining for and from the Semantic Web (MSW2004)
%U https://www.kde.cs.uni-kassel.de/hotho/pub/2004/msw2004_proceedings.pdf
2003
- 1.Hotho, A., Staab, S., Stumme, G.: Text Clustering Based on Background Knowledge. University of Karlsruhe, Institute AIFB (2003).Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. Standard partitional or agglomerative clustering methods efficiently compute results to this end. However, the bag of words representation used for these clustering methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. Also, it is mostly left to the user to find out why a particular partitioning has been achieved, because it is only specified extensionally. In order to deal with the two problems, we integrate background knowledge into the process of clustering text documents. First, we preprocess the texts, enriching their representations by background knowledge provided in a core ontology — in our application Wordnet. Then, we cluster the documents by a partitional algorithm. Our experimental evaluation on Reuters newsfeeds compares clustering results with pre-categorizations of news. In the experiments, improvements of results by background knowledge compared to the baseline can be shown for many interesting tasks. Second, the clustering partitions the large number of documents to a relatively small number of clusters, which may then be analyzed by conceptual clustering. In our approach, we applied Formal Concept Analysis. Conceptual clustering techniques are known to be too slow for directly clustering several hundreds of documents, but they give an intensional account of cluster results. They allow for a concise description of commonalities and distinctions of different clusters. With background knowledge they even find abstractions like “food” (vs. specializations like “beef” or “corn”). Thus, in our approach, partitional clustering reduces first the size of the problem such that it becomes tractable for conceptual clustering, which then facilitates the understanding of the results.
@techreport{hotho03textclustering,
abstract = {Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. Standard partitional or agglomerative clustering methods efficiently compute results to this end. However, the bag of words representation used for these clustering methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. Also, it is mostly left to the user to find out why a particular partitioning has been achieved, because it is only specified extensionally. In order to deal with the two problems, we integrate background knowledge into the process of clustering text documents. First, we preprocess the texts, enriching their representations by background knowledge provided in a core ontology — in our application Wordnet. Then, we cluster the documents by a partitional algorithm. Our experimental evaluation on Reuters newsfeeds compares clustering results with pre-categorizations of news. In the experiments, improvements of results by background knowledge compared to the baseline can be shown for many interesting tasks. Second, the clustering partitions the large number of documents to a relatively small number of clusters, which may then be analyzed by conceptual clustering. In our approach, we applied Formal Concept Analysis. Conceptual clustering techniques are known to be too slow for directly clustering several hundreds of documents, but they give an intensional account of cluster results. They allow for a concise description of commonalities and distinctions of different clusters. With background knowledge they even find abstractions like “food” (vs. specializations like “beef” or “corn”). Thus, in our approach, partitional clustering reduces first the size of the problem such that it becomes tractable for conceptual clustering, which then facilitates the understanding of the results.},
author = {Hotho, Andreas and Staab, Steffen and Stumme, Gerd},
institution = {University of Karlsruhe, Institute AIFB},
keywords = {ontologies},
title = {Text Clustering Based on Background Knowledge},
type = {Technical Report},
volume = 425,
year = 2003
}%0 Report
%1 hotho03textclustering
%A Hotho, Andreas
%A Staab, Steffen
%A Stumme, Gerd
%D 2003
%T Text Clustering Based on Background Knowledge
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003text.pdf
%V 425
%X Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. Standard partitional or agglomerative clustering methods efficiently compute results to this end. However, the bag of words representation used for these clustering methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. Also, it is mostly left to the user to find out why a particular partitioning has been achieved, because it is only specified extensionally. In order to deal with the two problems, we integrate background knowledge into the process of clustering text documents. First, we preprocess the texts, enriching their representations by background knowledge provided in a core ontology — in our application Wordnet. Then, we cluster the documents by a partitional algorithm. Our experimental evaluation on Reuters newsfeeds compares clustering results with pre-categorizations of news. In the experiments, improvements of results by background knowledge compared to the baseline can be shown for many interesting tasks. Second, the clustering partitions the large number of documents to a relatively small number of clusters, which may then be analyzed by conceptual clustering. In our approach, we applied Formal Concept Analysis. Conceptual clustering techniques are known to be too slow for directly clustering several hundreds of documents, but they give an intensional account of cluster results. They allow for a concise description of commonalities and distinctions of different clusters. With background knowledge they even find abstractions like “food” (vs. specializations like “beef” or “corn”). Thus, in our approach, partitional clustering reduces first the size of the problem such that it becomes tractable for conceptual clustering, which then facilitates the understanding of the results. - 1.Stumme, G., Ehrig, M., Handschuh, S., Hotho, A., Maedche, A., Motik, B., Oberle, D., Schmitz, C., Staab, S., Stojanovic, L., Stojanovic, N., Studer, R., Sure, Y., Volz, R., Zacharias, V.: The {K}arlsruhe view on ontologies. University of Karlsruhe, Institute AIFB (2003).
@techreport{stumme03,
author = {Stumme, Gerd and Ehrig, Marc and Handschuh, Siegfried and Hotho, Andreas and Maedche, Alexander and Motik, Boris and Oberle, Daniel and Schmitz, Christoph and Staab, Steffen and Stojanovic, Ljiljana and Stojanovic, Nenad and Studer, Rudi and Sure, York and Volz, Raphael and Zacharias, Valentin},
institution = {University of Karlsruhe, Institute AIFB},
keywords = {ontology},
title = {The {K}arlsruhe view on ontologies},
year = 2003
}%0 Report
%1 stumme03
%A Stumme, Gerd
%A Ehrig, Marc
%A Handschuh, Siegfried
%A Hotho, Andreas
%A Maedche, Alexander
%A Motik, Boris
%A Oberle, Daniel
%A Schmitz, Christoph
%A Staab, Steffen
%A Stojanovic, Ljiljana
%A Stojanovic, Nenad
%A Studer, Rudi
%A Sure, York
%A Volz, Raphael
%A Zacharias, Valentin
%D 2003
%T The {K}arlsruhe view on ontologies - 1.Ehrig, M., Schmitz, C., Staab, S., Tane, J., Tempich, C.: Towards Evaluation of Peer-to-Peer-based Distributed Information Management Systems. In: Proceedings of the AAAI Spring Symposium on Agent-Mediated Knowledge Management (AMKM-03). , Stanford (2003).
@inproceedings{ehrig2003towards,
address = {Stanford},
author = {Ehrig, Marc and Schmitz, Christoph and Staab, Steffen and Tane, Julien and Tempich, Christoph},
booktitle = {Proceedings of the AAAI Spring Symposium on Agent-Mediated Knowledge Management (AMKM-03)},
keywords = {p2p},
month = {03},
title = {Towards Evaluation of Peer-to-Peer-based Distributed Information Management Systems},
year = 2003
}%0 Conference Paper
%1 ehrig2003towards
%A Ehrig, Marc
%A Schmitz, Christoph
%A Staab, Steffen
%A Tane, Julien
%A Tempich, Christoph
%B Proceedings of the AAAI Spring Symposium on Agent-Mediated Knowledge Management (AMKM-03)
%C Stanford
%D 2003
%T Towards Evaluation of Peer-to-Peer-based Distributed Information Management Systems
%U https://www.kde.cs.uni-kassel.de/schmitz/publ/amkm_evaluation.pdf - 1.Nejdl, W., Wolpers, M., Siberski, W., Schmitz, C., Schlosser, M., Brunkhorst, I., Löser, A.: Super-Peer-Based Routing and Clustering Strategies for {RDF}-Based Peer-To-Peer Networks. In: Proceedings of the 12th International World Wide Web Conference. , Budapest (2003).
@inproceedings{nejdl2003superpeer,
address = {Budapest},
author = {Nejdl, Wolfgang and Wolpers, Martin and Siberski, Wolf and Schmitz, Christoph and Schlosser, Mario and Brunkhorst, Ingo and Löser, Alexander},
booktitle = {Proceedings of the 12th International World Wide Web Conference},
keywords = {p2p},
month = {05},
title = {Super-Peer-Based Routing and Clustering Strategies for {RDF}-Based Peer-To-Peer Networks},
year = 2003
}%0 Conference Paper
%1 nejdl2003superpeer
%A Nejdl, Wolfgang
%A Wolpers, Martin
%A Siberski, Wolf
%A Schmitz, Christoph
%A Schlosser, Mario
%A Brunkhorst, Ingo
%A Löser, Alexander
%B Proceedings of the 12th International World Wide Web Conference
%C Budapest
%D 2003
%T Super-Peer-Based Routing and Clustering Strategies for {RDF}-Based Peer-To-Peer Networks
%U https://www.kde.cs.uni-kassel.de/schmitz/publ/www03.pdf - 1.Stumme, G.: Off to New Shores -- Conceptual Knowledge Discovery and Processing. Intl. J. Human-Comuter Studies (IJHCS). 59, 287–325 (2003).In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits (1993). It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.
@article{stumme03off,
abstract = {In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits (1993). It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.},
author = {Stumme, G.},
journal = {Intl. J. Human-Comuter Studies (IJHCS)},
keywords = {Conceptual},
month = {09},
number = 3,
pages = {287-325},
title = {Off to New Shores -- Conceptual Knowledge Discovery and Processing},
volume = 59,
year = 2003
}%0 Journal Article
%1 stumme03off
%A Stumme, G.
%D 2003
%J Intl. J. Human-Comuter Studies (IJHCS)
%N 3
%P 287-325
%T Off to New Shores -- Conceptual Knowledge Discovery and Processing
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2003/stumme2003off.pdf
%V 59
%X In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits (1993). It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system. - 1.Berendt, B., Hotho, A., Mladenic, D., van Someren, M., Spiliopoulou, M., Stumme, G. eds.: Proceedings of the 1st European Web Mining Forum (EWMF 2003). Workshop at the 14th Europ. Conf. on Machine Learning (ECML’03) / 7th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’03), Cavtat/Dubrovnik, Croatia (2003).
@proceedings{Berendt03EWMFWS,
address = {Cavtat/Dubrovnik, Croatia},
editor = {Berendt, Bettina and Hotho, Andreas and Mladenic, Dunja and van Someren, Maarten and Spiliopoulou, Myra and Stumme, Gerd},
keywords = {pkdd},
month = {09},
publisher = {Workshop at the 14th Europ. Conf. on Machine Learning (ECML'03) / 7th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'03)},
title = {Proceedings of the 1st European Web Mining Forum (EWMF 2003)},
year = 2003
}%0 Conference Proceedings
%1 Berendt03EWMFWS
%C Cavtat/Dubrovnik, Croatia
%D 2003
%E Berendt, Bettina
%E Hotho, Andreas
%E Mladenic, Dunja
%E van Someren, Maarten
%E Spiliopoulou, Myra
%E Stumme, Gerd
%I Workshop at the 14th Europ. Conf. on Machine Learning (ECML'03) / 7th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'03)
%T Proceedings of the 1st European Web Mining Forum (EWMF 2003) - 1.Tane, J., Schmitz, C., Stumme, G., Staab, S., Studer, R.: The Courseware Watchdog: an Ontology-based tool for finding and organizing learning material. In: David, K. and Wegner, L. (eds.) Mobiles Lernen und Forschen - Beiträge der Fachtagung an der Universität. pp. 93–104. Kassel University Press (2003).Topics in education are changing with an ever faster pace. E-Learning resources tend to be more and more decentralised. Users need increasingly to be able to use the resources of the web. For this, they should have tools for finding and organizing information in a decentral way. In this, paper, we show how an ontology-based tool suite allows to make the most of the resources available on the web.
@inproceedings{tane03courseware,
abstract = {Topics in education are changing with an ever faster pace. E-Learning resources tend to be more and more decentralised. Users need increasingly to be able to use the resources of the web. For this, they should have tools for finding and organizing information in a decentral way. In this, paper, we show how an ontology-based tool suite allows to make the most of the resources available on the web.},
author = {Tane, Julien and Schmitz, Christoph and Stumme, Gerd and Staab, Steffen and Studer, R.},
booktitle = {Mobiles Lernen und Forschen - Beiträge der Fachtagung an der Universität},
editor = {David, Klaus and Wegner, Lutz},
keywords = {ontologies},
month = 11,
pages = {93-104},
publisher = {Kassel University Press},
title = {The Courseware Watchdog: an Ontology-based tool for finding and organizing learning material},
year = 2003
}%0 Conference Paper
%1 tane03courseware
%A Tane, Julien
%A Schmitz, Christoph
%A Stumme, Gerd
%A Staab, Steffen
%A Studer, R.
%B Mobiles Lernen und Forschen - Beiträge der Fachtagung an der Universität
%D 2003
%E David, Klaus
%E Wegner, Lutz
%I Kassel University Press
%P 93-104
%T The Courseware Watchdog: an Ontology-based tool for finding and organizing learning material
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2003/tane2003courseware.pdf
%X Topics in education are changing with an ever faster pace. E-Learning resources tend to be more and more decentralised. Users need increasingly to be able to use the resources of the web. For this, they should have tools for finding and organizing information in a decentral way. In this, paper, we show how an ontology-based tool suite allows to make the most of the resources available on the web. - 1.Hotho, A., Stumme, G. eds.: Lehren -- Lernen -- Wissen -- Adaptivität. Workshopwoche der GI-Fachgruppen/Arbeitskreise FGML, FGWM, ABIS, AKKD. , Universität Karlsruhe (2003).
@proceedings{hotho03lehren,
address = {Universität Karlsruhe},
editor = {Hotho, A. and Stumme, G.},
keywords = {akkd},
month = 10,
title = {Lehren -- Lernen -- Wissen -- Adaptivität. Workshopwoche der GI-Fachgruppen/Arbeitskreise FGML, FGWM, ABIS, AKKD},
year = 2003
}%0 Conference Proceedings
%1 hotho03lehren
%C Universität Karlsruhe
%D 2003
%E Hotho, A.
%E Stumme, G.
%T Lehren -- Lernen -- Wissen -- Adaptivität. Workshopwoche der GI-Fachgruppen/Arbeitskreise FGML, FGWM, ABIS, AKKD
%U http://km.aifb.uni-karlsruhe.de/ws/LLWA/ - 1.Hotho, A., Stumme, G. eds.: Lehren -- Lernen -- Wissen -- Adaptivit{ä}t (LLWA 2003). , Universit{ä}t Karlsruhe (2003).
@proceedings{hotho03llwa,
address = {Universit{ä}t Karlsruhe},
editor = {Hotho, Andreas and Stumme, Gerd},
keywords = {llwa},
month = 10,
note = {Proceedings der Workshopwoche der GI-Fachgruppen/Arbeitskreise FGML, FGWM, ABIS, AKKD},
title = {Lehren -- Lernen -- Wissen -- Adaptivit{ä}t (LLWA 2003)},
year = 2003
}%0 Conference Proceedings
%1 hotho03llwa
%C Universit{ä}t Karlsruhe
%D 2003
%E Hotho, Andreas
%E Stumme, Gerd
%T Lehren -- Lernen -- Wissen -- Adaptivit{ä}t (LLWA 2003) - 1.Hotho, A., Staab, S., Stumme, G.: Ontologies improve text document clustering. In: Proceedings of the 2003 IEEE International Conference on Data Mining. pp. 541–544 (Poster. IEEE {C}omputer {S}ociety, Melbourne, Florida (2003).
@inproceedings{hotho03ontologies,
address = {Melbourne, Florida},
author = {Hotho, Andreas and Staab, Steffen and Stumme, Gerd},
booktitle = {Proceedings of the 2003 IEEE International Conference on Data Mining},
keywords = {ontologies},
month = 11,
pages = {541-544 (Poster},
publisher = {IEEE {C}omputer {S}ociety},
title = {Ontologies improve text document clustering},
year = 2003
}%0 Conference Paper
%1 hotho03ontologies
%A Hotho, Andreas
%A Staab, Steffen
%A Stumme, Gerd
%B Proceedings of the 2003 IEEE International Conference on Data Mining
%C Melbourne, Florida
%D 2003
%I IEEE {C}omputer {S}ociety
%P 541-544 (Poster
%T Ontologies improve text document clustering
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003ontologies.pdf - 1.Hotho, A., Staab, S., Stumme, G.: Explaining Text Clustering Results using Semantic Structures. In: Proc. of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD. pp. 217–228 (2003).
@inproceedings{hotho_pkdd03,
author = {Hotho, A. and Staab, S. and Stumme, G.},
booktitle = {Proc. of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD},
keywords = {text},
pages = {217-228},
series = {LNCS},
title = {Explaining Text Clustering Results using Semantic Structures},
volume = 2838,
year = 2003
}%0 Conference Paper
%1 hotho_pkdd03
%A Hotho, A.
%A Staab, S.
%A Stumme, G.
%B Proc. of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD
%D 2003
%P 217-228
%T Explaining Text Clustering Results using Semantic Structures
%V 2838 - 1.Hotho, A., Stumme, G. eds.: Lehren -- Lernen -- Wissen -- Adaptivit{{ä}}t (LLWA 2003). , Universit{{ä}}t Karlsruhe (2003).
@proceedings{hotho03llwa,
address = {Universit{{ä}}t Karlsruhe},
editor = {Hotho, Andreas and Stumme, Gerd},
keywords = {llwa},
month = 10,
note = {Proceedings der Workshopwoche der GI-Fachgruppen/Arbeitskreise FGML, FGWM, ABIS, AKKD},
title = {Lehren -- Lernen -- Wissen -- Adaptivit{{ä}}t (LLWA 2003)},
year = 2003
}%0 Conference Proceedings
%1 hotho03llwa
%C Universit{{ä}}t Karlsruhe
%D 2003
%E Hotho, Andreas
%E Stumme, Gerd
%T Lehren -- Lernen -- Wissen -- Adaptivit{{ä}}t (LLWA 2003) - 1.Lauser, B., Hotho, A.: Automatic multi-label subject indexing in a multilingual environment. In: Proc. of the 7th European Conference in Research and Advanced Technology for Digital Libraries, ECDL 2003. pp. 140–151. Springer (2003).
@inproceedings{lauser03,
author = {Lauser, Boris and Hotho, Andreas},
booktitle = {Proc. of the 7th European Conference in Research and Advanced Technology for Digital Libraries, ECDL 2003},
keywords = {ontology},
pages = {140-151},
publisher = {Springer},
series = {LNCS},
title = {Automatic multi-label subject indexing in a multilingual environment},
volume = 2769,
year = 2003
}%0 Conference Paper
%1 lauser03
%A Lauser, Boris
%A Hotho, Andreas
%B Proc. of the 7th European Conference in Research and Advanced Technology for Digital Libraries, ECDL 2003
%D 2003
%I Springer
%P 140-151
%T Automatic multi-label subject indexing in a multilingual environment
%V 2769 - 1.Cole, R.J., Eklund, P.W., Stumme, G.: Document Retrieval for Email Search and Discovery using Formal Concept Analysis. Journal of Applied Artificial Intelligence (AAI). 17, 257–280 (2003).This paper discusses an document discovery tool based on conceptual clustering by formal concept analysis. The program allows users to navigate email using a visual lattice metaphor rather than a tree. It implements a virtual file structure over email where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in email discovery. The system described provides more flexibility in retrieving stored emails than what is normally available in email clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.
@article{cole03document,
abstract = {This paper discusses an document discovery tool based on conceptual clustering by formal concept analysis. The program allows users to navigate email using a visual lattice metaphor rather than a tree. It implements a virtual file structure over email where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in email discovery. The system described provides more flexibility in retrieving stored emails than what is normally available in email clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.},
author = {Cole, Richard J. and Eklund, Peter W. and Stumme, Gerd},
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%X This paper discusses an document discovery tool based on conceptual clustering by formal concept analysis. The program allows users to navigate email using a visual lattice metaphor rather than a tree. It implements a virtual file structure over email where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in email discovery. The system described provides more flexibility in retrieving stored emails than what is normally available in email clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections. - 1.Oberle, D., Berendt, B., Hotho, A., Gonzalez, J.: Conceptual User Tracking. In: Ruiz, E.M., Segovia, J., and Szczepaniak, P.S. (eds.) Advances in Web Intelligence, First International Atlantic Web Intelligence Conference, AWIC 2003, Madrid, Spain, May 5-6, 2003, Proceedings. pp. 142–154. Springer (2003).
@inproceedings{awic2003,
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%V 2663 - 1.Reimer, U., Abecker, A., Staab, A., Stumme, G. eds.: Professionelles Wissensmanagement -- Erfahrungen und Visionen. Proc. WM 2003. Gesellschaft für Informatik, Bonn (2003).
@proceedings{reimer03professionelles,
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%V 28 - 1.Hereth, J., Stumme, G., Wille, R., Wille, U.: Conceptual Knowledge Discovery - a Human-Centered Approach. Journal of Applied Artificial Intelligence (AAI). 17, 281–301 (2003).In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. We dicuss how the management system TOSCANA for conceptual information systems supports CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, Chianti.
@article{hereth03conceptual,
abstract = {In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. We dicuss how the management system TOSCANA for conceptual information systems supports CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, Chianti.},
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%X In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. We dicuss how the management system TOSCANA for conceptual information systems supports CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, Chianti. - 1.Hotho, A., Stumme, G., Studer, R., Volz, R.: Semantic Web -- State of the Art and Future Directions. Künstliche Intelligenz. 5–9 (2003).The paper presents the vision of the Se- mantic Web and describes ontologies and associated metadata as the building blocks of the SemanticWeb. Current research topics and promising application ar- eas are discussed as well.
@article{hotho03semantic,
abstract = {The paper presents the vision of the Se- mantic Web and describes ontologies and associated metadata as the building blocks of the SemanticWeb. Current research topics and promising application ar- eas are discussed as well.},
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%X The paper presents the vision of the Se- mantic Web and describes ontologies and associated metadata as the building blocks of the SemanticWeb. Current research topics and promising application ar- eas are discussed as well. - 1.Staab, S., Hotho, A.: Ontology-based Text Document Clustering. In: Intelligent Information Processing and Web Mining, Proceedings of the International IIS: IIPWM’03 Conference held in Zakopane. pp. 451–452 (2003).
@inproceedings{conf/iis/StaabH03,
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booktitle = {Intelligent Information Processing and Web Mining, Proceedings of the International IIS: IIPWM'03 Conference held in Zakopane},
keywords = {ontology},
pages = {451-452},
title = {Ontology-based Text Document Clustering.},
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%@ 3-540-00843-8 - 1.Ganter, B., Stumme, G.: Creation and Merging of Ontology Top-Levels. In: de Moor, A., Lex, W., and Ganter, B. (eds.) Conceptual Structures for Knowledge Creation and Communication. pp. 131–145. Springer, Heidelberg (2003).We provide a new method for systematically structuring the top-down level of ontologies. It is based on an interactive, top--down knowledge acquisition process, which assures that the knowledge engineer considers all possible cases while avoiding redundant acquisition. The method is suited especially for creating/merging the top part(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.
@inproceedings{ganter03creation,
abstract = {We provide a new method for systematically structuring the top-down level of ontologies. It is based on an interactive, top--down knowledge acquisition process, which assures that the knowledge engineer considers all possible cases while avoiding redundant acquisition. The method is suited especially for creating/merging the top part(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.},
address = {Heidelberg},
author = {Ganter, Bernhard and Stumme, Gerd},
booktitle = {Conceptual Structures for Knowledge Creation and Communication.},
editor = {de Moor, Aldo and Lex, Wilfried and Ganter, Bernhard},
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pages = {131-145},
publisher = {Springer},
series = {LNAI},
title = {Creation and Merging of Ontology Top-Levels},
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%A Ganter, Bernhard
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%X We provide a new method for systematically structuring the top-down level of ontologies. It is based on an interactive, top--down knowledge acquisition process, which assures that the knowledge engineer considers all possible cases while avoiding redundant acquisition. The method is suited especially for creating/merging the top part(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level. - 1.Stefani, S., Adamczak, W.: A web based conference tool developed with SeSAMe, http://www.svenstefani.de/publ/eunis2003/Eunis2003_pp97_final.ppt, (2003).
@misc{eunis2003ss,
address = {EUNIS 2003, Niederlande},
author = {Stefani, Sven and Adamczak, Wolfgang},
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%U http://www.svenstefani.de/publ/eunis2003/Eunis2003_pp97_final.ppt - 1.Agarwal, S., Fankhauser, P., Gonzalez-Ollala, J., Hartmann, J., Hollfelder, S., Jameson, A., Klink, S., Lehti, P., Ley, M., Rabbidge, E., Schwarzkopf, E., Shrestha, N., Stojanovic, N., Studer, R., Stumme, G., Walter, B.: Semantic Methods and Tools for Information Portals. In: Dittrich, K., König, W., Oberweis, A., Rannenberg, K., and Wahlster, W. (eds.) INFORMATIK 2003 -- Innovative Informatikanwendungen (Band 1). pp. 116–131. Gesellschaft für Informatik, Bonn (2003).The paper describes a set of approaches for representing and accessing information within a semantically structured information portal, while offering the possibility to integrate own information. It discusses research performed within the project `Semantic Methods and Tools for Information Portals (SemIPort)'. In particular, it focuses on (1) the development of scalable storing, processing and querying methods for semantic data, (2) visualization and browsing of complex data inventories, (3) personalization and agent-based interaction, and (4) the enhancement of web mining approaches for use within a semantics-based portal.
@inproceedings{agarwal03semantic,
abstract = {The paper describes a set of approaches for representing and accessing information within a semantically structured information portal, while offering the possibility to integrate own information. It discusses research performed within the project `Semantic Methods and Tools for Information Portals (SemIPort)'. In particular, it focuses on (1) the development of scalable storing, processing and querying methods for semantic data, (2) visualization and browsing of complex data inventories, (3) personalization and agent-based interaction, and (4) the enhancement of web mining approaches for use within a semantics-based portal.},
address = {Bonn},
author = {Agarwal, Sudhir and Fankhauser, Peter and Gonzalez-Ollala, Jorge and Hartmann, Jens and Hollfelder, Silvia and Jameson, Anthony and Klink, Stefan and Lehti, Patrick and Ley, Michael and Rabbidge, Emma and Schwarzkopf, Eric and Shrestha, Nitesh and Stojanovic, Nenad and Studer, Rudi and Stumme, Gerd and Walter, Bernd},
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}%0 Conference Paper
%1 agarwal03semantic
%A Agarwal, Sudhir
%A Fankhauser, Peter
%A Gonzalez-Ollala, Jorge
%A Hartmann, Jens
%A Hollfelder, Silvia
%A Jameson, Anthony
%A Klink, Stefan
%A Lehti, Patrick
%A Ley, Michael
%A Rabbidge, Emma
%A Schwarzkopf, Eric
%A Shrestha, Nitesh
%A Stojanovic, Nenad
%A Studer, Rudi
%A Stumme, Gerd
%A Walter, Bernd
%B INFORMATIK 2003 -- Innovative Informatikanwendungen (Band 1)
%C Bonn
%D 2003
%E Dittrich, K.
%E König, W.
%E Oberweis, A.
%E Rannenberg, K.
%E Wahlster, W.
%I Gesellschaft für Informatik
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%T Semantic Methods and Tools for Information Portals
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%X The paper describes a set of approaches for representing and accessing information within a semantically structured information portal, while offering the possibility to integrate own information. It discusses research performed within the project `Semantic Methods and Tools for Information Portals (SemIPort)'. In particular, it focuses on (1) the development of scalable storing, processing and querying methods for semantic data, (2) visualization and browsing of complex data inventories, (3) personalization and agent-based interaction, and (4) the enhancement of web mining approaches for use within a semantics-based portal. - 1.Hotho, A., Staab, S., Stumme, G.: WordNet improves text document clustering. In: Proc. of the SIGIR 2003 Semantic Web Workshop. , Toronto, Canada (2003).
@inproceedings{hotho_sigir03,
address = {Toronto, Canada},
author = {Hotho, A. and Staab, S. and Stumme, G.},
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keywords = {ontology},
title = {WordNet improves text document clustering},
year = 2003
}%0 Conference Paper
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%A Hotho, A.
%A Staab, S.
%A Stumme, G.
%B Proc. of the SIGIR 2003 Semantic Web Workshop
%C Toronto, Canada
%D 2003
%T WordNet improves text document clustering
%U https://www.kde.cs.uni-kassel.de/hotho/pub/hothoetal_sigir_ws_sem_web.pdf - 1.Hotho, A., Maedche, A., Staab, S., Zacharias, V.: On Knowledgeable Unsupervised Text Mining. In: Text Mining. pp. 131–152 (2003).
@incollection{hotho03tm,
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%T On Knowledgeable Unsupervised Text Mining - 1.Studer, R., Stumme, G., Handschuh, S., Hotho, A., Motik, B.: Building and Using the Semantic Web. In: New Trends in Knowledge Processing -- Data Mining, Semantic Web and Computational. pp. 31–34. , Osaka, Japan (2003).
@inproceedings{studer03building,
address = {Osaka, Japan},
author = {Studer, Rudi and Stumme, Gerd and Handschuh, Siegfried and Hotho, Andreas and Motik, B.},
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month = {03},
pages = {31-34},
title = {Building and Using the Semantic Web},
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}%0 Conference Paper
%1 studer03building
%A Studer, Rudi
%A Stumme, Gerd
%A Handschuh, Siegfried
%A Hotho, Andreas
%A Motik, B.
%B New Trends in Knowledge Processing -- Data Mining, Semantic Web and Computational
%C Osaka, Japan
%D 2003
%P 31-34
%T Building and Using the Semantic Web
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2003/Sanken03.pdf
2002
- 1.Fernandez-Lopez, M., Gomez-Perez, A., Euzenat, J., Gangemi, A., Kalfoglou, Y., Pisanelli, D., Schorlemmer, M., Steve, G., Stojanovic, L., Stumme, G., Sure, Y.: A survey on methodologies for developing, maintaining, integration, evaluation and reengineering ontologies. Universidad Politecnia de Madrid (2002).
@techreport{fernandez02survey,
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institution = {Universidad Politecnia de Madrid},
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title = {A survey on methodologies for developing, maintaining, integration, evaluation and reengineering ontologies},
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%A Steve, G.
%A Stojanovic, Ljilajana
%A Stumme, Gerd
%A Sure, York
%D 2002
%T A survey on methodologies for developing, maintaining, integration, evaluation and reengineering ontologies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/OntoWeb_Del_1-4.pdf - 1.Berendt, B., Hotho, A., Stumme, G. eds.: Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf. on Machine Learning (ECML’02) / 6th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’02). , Helsinki, Finland (2002).
@proceedings{berendt02semantic,
address = {Helsinki, Finland},
editor = {Berendt, B. and Hotho, A. and Stumme, G.},
keywords = {pkdd},
month = {08},
title = {Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf. on Machine Learning (ECML'02) / 6th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'02)},
year = 2002
}%0 Conference Proceedings
%1 berendt02semantic
%C Helsinki, Finland
%D 2002
%E Berendt, B.
%E Hotho, A.
%E Stumme, G.
%T Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf. on Machine Learning (ECML'02) / 6th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'02)
%U http://km.aifb.uni-karlsruhe.de/ws/semwebmine2002/online_html - 1.Ganter, B., Stumme, G.: Creation and Merging of Ontology Top-Levels. In: Maedche, A., Sattler, K.-U., and Stumme, G. (eds.) Information Integration and Mining in Databases and on the Web. pp. 37–52. , Karlsruhe (2002).We provide a new method for systematically structuring the top-down level of ontologies. It is based on an interactive, top-down knowledge acquisition process, which assures that the knowledge engineer considers all possible cases while avoiding redundant acquisition. The method is suited especially for creating/merging the top part(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.
@inproceedings{ganter02creation,
abstract = {We provide a new method for systematically structuring the top-down level of ontologies. It is based on an interactive, top-down knowledge acquisition process, which assures that the knowledge engineer considers all possible cases while avoiding redundant acquisition. The method is suited especially for creating/merging the top part(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.},
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%A Stumme, G.
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%E Maedche, A.
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%E Stumme, G.
%P 37-52
%T Creation and Merging of Ontology Top-Levels
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%X We provide a new method for systematically structuring the top-down level of ontologies. It is based on an interactive, top-down knowledge acquisition process, which assures that the knowledge engineer considers all possible cases while avoiding redundant acquisition. The method is suited especially for creating/merging the top part(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level. - 1.Duquenne, V., Ganter, B., Liquiere, M., Nguifo, E.M., Stumme, G. eds.: Advances in Formal Concept Analysis for Knowledge Discovery in Databases. Proc. Workshop FCAKDD of the 15th European Conference on Artificial Intelligence (ECAI 2002). , Lyon, France (2002).
@proceedings{duquenne02advanced,
address = {Lyon, France},
editor = {Duquenne, V. and Ganter, B. and Liquiere, M. and Nguifo, E. M. and Stumme, G.},
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title = {Advances in Formal Concept Analysis for Knowledge Discovery in Databases. Proc. Workshop FCAKDD of the 15th European Conference on Artificial Intelligence (ECAI 2002)},
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%U http://www.lirmm.fr/~liquiere/Documents/FCAKDDProceedings2002.pdf - 1.Becker, P., Hereth, J., Stumme, G.: Toscana{J}: An Open Source Tool for Qualitative Data Analysis. In: Duquenne, V., Ganter, B., Liquiere, M., Nguifo, E.M., and Stumme, G. (eds.) Advances in Formal Concept Analysis for Knowledge Discovery in Databases. pp. 1–2. , Lyon, France (2002).
@inproceedings{becker02toscana,
address = {Lyon, France},
author = {Becker, P. and Hereth, J. and Stumme, G.},
booktitle = {Advances in Formal Concept Analysis for Knowledge Discovery in Databases.},
editor = {Duquenne, V. and Ganter, B. and Liquiere, M. and Nguifo, E. M. and Stumme, G.},
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title = {Toscana{J}: An Open Source Tool for Qualitative Data Analysis},
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}%0 Conference Paper
%1 becker02toscana
%A Becker, P.
%A Hereth, J.
%A Stumme, G.
%B Advances in Formal Concept Analysis for Knowledge Discovery in Databases.
%C Lyon, France
%D 2002
%E Duquenne, V.
%E Ganter, B.
%E Liquiere, M.
%E Nguifo, E. M.
%E Stumme, G.
%P 1-2
%T Toscana{J}: An Open Source Tool for Qualitative Data Analysis
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/FCAKDD02.pdf - 1.Gonzalez-Olalla, J., Stumme, G.: Semantic Methods and Tools for Information Portals - The {S}em{IP}ort Project (Project Description). In: Berendt, B., Hotho, A., and Stumme, G. (eds.) Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf. p. 90. , Helsinki (2002).
@inproceedings{gonzalez02semantic,
address = {Helsinki},
author = {Gonzalez-Olalla, J. and Stumme, G.},
booktitle = {Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf.},
editor = {Berendt, B. and Hotho, A. and Stumme, G.},
keywords = {ontologies},
month = {08},
pages = 90,
title = {Semantic Methods and Tools for Information Portals - The {S}em{IP}ort Project (Project Description)},
year = 2002
}%0 Conference Paper
%1 gonzalez02semantic
%A Gonzalez-Olalla, J.
%A Stumme, G.
%B Semantic Web Mining. Proc. of the Semantic Web Mining Workshop of the 13th Europ. Conf.
%C Helsinki
%D 2002
%E Berendt, B.
%E Hotho, A.
%E Stumme, G.
%P 90
%T Semantic Methods and Tools for Information Portals - The {S}em{IP}ort Project (Project Description)
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/gonzalez2002semantic.pdf - 1.Stumme, G.: Efficient Data Mining Based on Formal Concept Analysis. In: Hameurlain, A., Cicchetti, R., and Traunmüller, R. (eds.) Database and Expert Systems Applications. Proc. DEXA 2002. pp. 534–546. Springer, Heidelberg (2002).
@inproceedings{stumme02efficient,
address = {Heidelberg},
author = {Stumme, G.},
booktitle = {Database and Expert Systems Applications. Proc. DEXA 2002},
editor = {Hameurlain, A. and Cicchetti, R. and Traunmüller, R.},
keywords = {itemsets},
pages = {534-546},
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}%0 Conference Paper
%1 stumme02efficient
%A Stumme, G.
%B Database and Expert Systems Applications. Proc. DEXA 2002
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%D 2002
%E Hameurlain, A.
%E Cicchetti, R.
%E Traunmüller, R.
%I Springer
%P 534-546
%T Efficient Data Mining Based on Formal Concept Analysis
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/DEXA02.pdf
%V 2453 - 1.Ehrig, M., Handschuh, S., Hotho, A., Maedche, A., Motik, B., Oberle, D., Schmitz, C., Staab, S., Stojanovic, L., Stojanovic, N., Studer, R., Stumme, G., Sure, Y., Tane, J., Volz, R., Zacharias, V.: {KAON} - Towards a large scale {S}emantic {W}eb. In: Bauknecht, K., Tjoa, A.M., and Quirchmayr, G. (eds.) Proc. E-Commerce and Web Technologies, Third International Conference, EC-Web 2002. Springer, Aix-en-Provence %, France (2002).
@inproceedings{ehrig2002kaon,
address = {Aix-en-Provence %, France},
author = {Ehrig, Marc and Handschuh, Siegfried and Hotho, Andreas and Maedche, Alexander and Motik, Boris and Oberle, Daniel and Schmitz, Christoph and Staab, Steffen and Stojanovic, Ljiljana and Stojanovic, Nenad and Studer, Rudi and Stumme, Gerd and Sure, York and Tane, Julien and Volz, Raphael and Zacharias, Valentin},
booktitle = {Proc. E-Commerce and Web Technologies, Third International Conference, EC-Web 2002},
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month = {09},
number = 2455,
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series = {LNCS},
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}%0 Conference Paper
%1 ehrig2002kaon
%A Ehrig, Marc
%A Handschuh, Siegfried
%A Hotho, Andreas
%A Maedche, Alexander
%A Motik, Boris
%A Oberle, Daniel
%A Schmitz, Christoph
%A Staab, Steffen
%A Stojanovic, Ljiljana
%A Stojanovic, Nenad
%A Studer, Rudi
%A Stumme, Gerd
%A Sure, York
%A Tane, Julien
%A Volz, Raphael
%A Zacharias, Valentin
%B Proc. E-Commerce and Web Technologies, Third International Conference, EC-Web 2002
%C Aix-en-Provence %, France
%D 2002
%E Bauknecht, Kurt
%E Tjoa, A. Min
%E Quirchmayr, Gerald
%I Springer
%N 2455
%T {KAON} - Towards a large scale {S}emantic {W}eb - 1.Hartmann, J., Hotho, A., Stumme, G.: Semantic Web Mining for Building Information Portals (Position Paper). In: Proc. Arbeitskreistreffen Knowledge Discovery. , Oldenburg (2002).
@inproceedings{hartmann02semanticweb,
address = {Oldenburg},
author = {Hartmann, J. and Hotho, A. and Stumme, G.},
booktitle = {Proc. Arbeitskreistreffen Knowledge Discovery},
keywords = {ontologies},
month = {09},
title = {Semantic Web Mining for Building Information Portals (Position Paper)},
year = 2002
}%0 Conference Paper
%1 hartmann02semanticweb
%A Hartmann, J.
%A Hotho, A.
%A Stumme, G.
%B Proc. Arbeitskreistreffen Knowledge Discovery
%C Oldenburg
%D 2002
%T Semantic Web Mining for Building Information Portals (Position Paper)
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/hartmann2002semanticweb.pdf - 1.Schmitz, C., Staab, S., Studer, R., Stumme, G., Tane, J.: Accessing Distributed Learning Repositories through a {C}ourseware {W}atchdog. In: Proc. E-Learn 2002: World Conference on E-Learning in Corporate, Government, Healthcare, \& Higher Education. , Montreal (2002).
@inproceedings{schmitz2002accessing,
address = {Montreal},
author = {Schmitz, Christoph and Staab, Steffen and Studer, Rudi and Stumme, Gerd and Tane, Julien},
booktitle = {Proc. E-Learn 2002: World Conference on E-Learning in Corporate, Government, Healthcare, \& Higher Education},
keywords = {p2p},
month = 10,
title = {Accessing Distributed Learning Repositories through a {C}ourseware {W}atchdog},
year = 2002
}%0 Conference Paper
%1 schmitz2002accessing
%A Schmitz, Christoph
%A Staab, Steffen
%A Studer, Rudi
%A Stumme, Gerd
%A Tane, Julien
%B Proc. E-Learn 2002: World Conference on E-Learning in Corporate, Government, Healthcare, \& Higher Education
%C Montreal
%D 2002
%T Accessing Distributed Learning Repositories through a {C}ourseware {W}atchdog
%U https://www.kde.cs.uni-kassel.de/schmitz/publ/elearn02.pdf - 1.Stumme, G., Berendt, B., Hotho, A.: Usage Mining for and on the Semantic Web. In: Proc. NSF Workshop on Next Generation Data Mining. pp. 77–86. , Baltimore (2002).
@inproceedings{stumme02usage,
address = {Baltimore},
author = {Stumme, G. and Berendt, B. and Hotho, A.},
booktitle = {Proc. NSF Workshop on Next Generation Data Mining},
keywords = 2002,
month = 11,
pages = {77-86},
title = {Usage Mining for and on the Semantic Web},
year = 2002
}%0 Conference Paper
%1 stumme02usage
%A Stumme, G.
%A Berendt, B.
%A Hotho, A.
%B Proc. NSF Workshop on Next Generation Data Mining
%C Baltimore
%D 2002
%P 77-86
%T Usage Mining for and on the Semantic Web
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/NSF-NGDM02.pdf - 1.Stumme, G.: E-{L}earning: vom {N}ürnberger {T}richter zum weltweiten {N}etz. Karlsruher Transfer. 27, 14–17 (2002).
@article{stumme02elearning,
author = {Stumme, G.},
journal = {Karlsruher Transfer},
keywords = {eLearning},
pages = {14-17},
title = {E-{L}earning: vom {N}ürnberger {T}richter zum weltweiten {N}etz},
volume = 27,
year = 2002
}%0 Journal Article
%1 stumme02elearning
%A Stumme, G.
%D 2002
%J Karlsruher Transfer
%P 14-17
%T E-{L}earning: vom {N}ürnberger {T}richter zum weltweiten {N}etz
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/KarlsruherTransfer02.pdf
%V 27 - 1.Stumme, G.: Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge. In: Becker, J. and Knackstedt, R. (eds.) Wissensmanagement mit Referenzmodellen -- Konzepte für die Anwendungssystem- und Organisationsgestaltung. pp. 163–174. Physica, Heidelberg (2002).
@incollection{stumme02using,
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booktitle = {Wissensmanagement mit Referenzmodellen -- Konzepte für die Anwendungssystem- und Organisationsgestaltung},
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pages = {163-174},
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title = {Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge},
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%T Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2001/REFMOD01.ps - 1.Bastide, Y., Taouil, R., Pasquier, N., Stumme, G., Lakhal, L.: Pascal: un alogorithme d’extraction des motifs fréquents. Technique et Science Informatiques (TSI). 21, 65–95 (2002).
@article{bastide02unalogorithme,
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}%0 Journal Article
%1 bastide02unalogorithme
%A Bastide, Y.
%A Taouil, R.
%A Pasquier, N.
%A Stumme, G.
%A Lakhal, L.
%D 2002
%J Technique et Science Informatiques (TSI)
%N 1
%P 65-95
%T Pascal: un alogorithme d'extraction des motifs fréquents
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2001/TSI01.pdf
%V 21 - 1.Stumme, G.: Formal Concept Analysis on its Way from Mathematics to Computer Science. In: Priss, U., Corbett, D., and Angelova, G. (eds.) Conceptual Structures: Integration and Interfaces. pp. 2–19. Springer, Heidelberg (2002).
@inproceedings{stumme02formalconcept,
address = {Heidelberg},
author = {Stumme, G.},
booktitle = {Conceptual Structures: Integration and Interfaces},
editor = {Priss, U. and Corbett, D. and Angelova, G.},
keywords = {mathematik},
note = {Invited Talk, summary of \cite{stumme03offtonew}},
pages = {2-19},
publisher = {Springer},
series = {LNAI},
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}%0 Conference Paper
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%A Stumme, G.
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%E Priss, U.
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%U https://www.kde.cs.uni-kassel.de/stumme/papers/2002/ICCS02.pdf
%V 2393 - 1.Bozsak, E., Ehrig, M., Handschuh, S., Hotho, A., Maedche, A., Motik, B., Oberle, D., Schmitz, C., Staab, S., Stojanovic, L., Stojanovic, N., Studer, R., Stumme, G., Sure, Y., Tane, J., Volz, R., Zacharias, V.: KAON - Towards a Large Scale Semantic Web. In: Bauknecht, K., Tjoa, A.M., and Quirchmayr, G. (eds.) E-Commerce and Web Technologies, Third International Conference, EC-Web 2002, Proceedings. pp. 304–313. Springer, Aix-en-Provence, France (2002).
@inproceedings{kaon_def2002,
address = {Berlin},
author = {Bozsak, E. and Ehrig, M. and Handschuh, S. and Hotho, A. and Maedche, A. and Motik, B. and Oberle, D. and Schmitz, C. and Staab, S. and Stojanovic, L. and Stojanovic, N. and Studer, R. and Stumme, G. and Sure, Y. and Tane, J. and Volz, R. and Zacharias, V.},
booktitle = {E-Commerce and Web Technologies, Third International Conference, EC-Web 2002, Proceedings},
editor = {Bauknecht, K. and Tjoa, A. Min and Quirchmayr, G.},
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pages = {304--313},
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series = {LNCS},
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}%0 Conference Paper
%1 kaon_def2002
%A Bozsak, E.
%A Ehrig, M.
%A Handschuh, S.
%A Hotho, A.
%A Maedche, A.
%A Motik, B.
%A Oberle, D.
%A Schmitz, C.
%A Staab, S.
%A Stojanovic, L.
%A Stojanovic, N.
%A Studer, R.
%A Stumme, G.
%A Sure, Y.
%A Tane, J.
%A Volz, R.
%A Zacharias, V.
%B E-Commerce and Web Technologies, Third International Conference, EC-Web 2002, Proceedings
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%D 2002
%E Bauknecht, K.
%E Tjoa, A. Min
%E Quirchmayr, G.
%I Springer
%P 304--313
%T KAON - Towards a Large Scale Semantic Web
%V 2455 - 1.Hotho, A., Maedche, A., Staab, S.: Text Clustering Based on Good Aggregations. K{{ü}}nstliche Intelligenz (KI). 16, 48–54 (2002).
@article{hotho02ki,
author = {Hotho, Andreas and Maedche, Alexander and Staab, Steffen},
journal = {K{{ü}}nstliche Intelligenz (KI)},
keywords = {ontology},
number = 4,
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title = {Text Clustering Based on Good Aggregations},
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year = 2002
}%0 Journal Article
%1 hotho02ki
%A Hotho, Andreas
%A Maedche, Alexander
%A Staab, Steffen
%D 2002
%J K{{ü}}nstliche Intelligenz (KI)
%N 4
%P 48-54
%T Text Clustering Based on Good Aggregations
%U http://www.aifb.uni-karlsruhe.de/WBS/aho/pub/Ontology_based_Text_Document_Clustering_2002.pdf
%V 16 - 1.Stumme, G., Taouil, R., Bastide, Y., Pasquier, N., Lakhal, L.: Computing iceberg concept lattices with TITANIC. Data \& Knowledge Engineering. 42, 189–222 (2002). https://doi.org/10.1016/S0169-023X(02)00057-5.We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data.
@article{stumme2002computing,
abstract = {We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data.},
address = {Amsterdam, The Netherlands, The Netherlands},
author = {Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi},
journal = {Data \& Knowledge Engineering},
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pages = {189--222},
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}%0 Journal Article
%1 stumme2002computing
%A Stumme, Gerd
%A Taouil, Rafik
%A Bastide, Yves
%A Pasquier, Nicolas
%A Lakhal, Lotfi
%C Amsterdam, The Netherlands, The Netherlands
%D 2002
%I Elsevier Science Publishers B. V.
%J Data \& Knowledge Engineering
%N 2
%P 189--222
%R 10.1016/S0169-023X(02)00057-5
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%U http://portal.acm.org/citation.cfm?id=606457
%V 42
%X We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data. - 1.Stumme, G., Taouil, R., Bastide, Y., Pasqier, N., Lakhal, L.: Computing Iceberg Concept Lattices with {Titanic}. {J.} Data and KnowledgeEngineering (DKE). 42, 189–222 (2002).
@article{stumme02computing,
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%V 42 - 1.Hotho, A., Stumme, G.: Conceptual Clustering of Text Clusters. In: Proceedings of FGML Workshop. pp. 37–45. Special Interest Group of German Informatics Society (FGML --- Fachgruppe Maschinelles Lernen der GI e.V.) (2002).
@inproceedings{hotho_fgml02,
author = {Hotho, A. and Stumme, G.},
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%U \url{http://www.aifb.uni-karlsruhe.de/WBS/aho/pub/tc_fca_2002_submit.pdf} - 1.Berendt, B., Hotho, A., Stumme, G.: Towards Semantic Web Mining. In: Horrocks, I. and Hendler, J.A. (eds.) {P}roceedings of the {F}irst {I}nternational {S}emantic {W}eb {C}onference: The {S}emantic {W}eb ({ISWC} 2002). pp. 264–278. Springer, Sardinia, Italy (2002).
@inproceedings{semweb-mining-iswc02,
address = {Sardinia, Italy},
author = {Berendt, B. and Hotho, A. and Stumme, G.},
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%V 2342 - 1.Hotho, A., Maedche, A., Staab, S., Zacharias, V.: On Knowledgeable Unsupervised Text Mining. In: Proc. of Text Mining Workshop (2002).
@inproceedings{hotho02textws,
author = {Hotho, Andreas and Maedche, Alexander and Staab, Steffen and Zacharias, Valentin},
booktitle = {Proc. of Text Mining Workshop},
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title = {On Knowledgeable Unsupervised Text Mining},
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%A Hotho, Andreas
%A Maedche, Alexander
%A Staab, Steffen
%A Zacharias, Valentin
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%U http://www.aifb.uni-karlsruhe.de/WBS/aho/pub/txt_mining_ws_2002.pdf - 1.Berendt, B., Hotho, A., Stumme, G. eds.: Semantic Web Mining. Workshop at 13th Europ. Conf. on Machine Learning (ECML’02) / 6th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’02), Helsinki (2002).
@proceedings{WS_BHS02,
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booktitle = {Proc. of the Semantic Web Mining Workshop},
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2001
- 1.Gronau, N., Stumme, G. eds.: Methoden und Techniken der Wissensverarbeitung. Workshop der 1. Tagung Professionelles Wissensmanagement -- Erfahrungen und Visionen. Shaker, Aachen (2001).
@proceedings{gronau01methoden,
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editor = {Gronau, N. and Stumme, G.},
keywords = {wissensmanagement},
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title = {Methoden und Techniken der Wissensverarbeitung. Workshop der 1. Tagung Professionelles Wissensmanagement -- Erfahrungen und Visionen},
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%C Aachen
%D 2001
%E Gronau, N.
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%I Shaker
%P 287-378
%T Methoden und Techniken der Wissensverarbeitung. Workshop der 1. Tagung Professionelles Wissensmanagement -- Erfahrungen und Visionen
%U http://wm2001.aifb.uni-karlsruhe.de/ws/ws7.html - 1.Stumme, G., Taouil, R., Bastide, Y., Pasquier, N., Lakhal, L.: Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis. In: Baader, F., Brewker, G., and Eiter, T. (eds.) KI 2001: Advances in Artificial Intelligence. KI 2001. pp. 335–350. Springer, Heidelberg (2001).
@inproceedings{stumme01intelligent,
address = {Heidelberg},
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Pasquier, N. and Lakhal, L.},
booktitle = {KI 2001: Advances in Artificial Intelligence. KI 2001},
editor = {Baader, F. and Brewker, G. and Eiter, T.},
keywords = {itemsets},
pages = {335-350},
publisher = {Springer},
series = {LNAI},
title = {Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis},
volume = 2174,
year = 2001
}%0 Conference Paper
%1 stumme01intelligent
%A Stumme, G.
%A Taouil, R.
%A Bastide, Y.
%A Pasquier, N.
%A Lakhal, L.
%B KI 2001: Advances in Artificial Intelligence. KI 2001
%C Heidelberg
%D 2001
%E Baader, F.
%E Brewker, G.
%E Eiter, T.
%I Springer
%P 335-350
%T Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2001/KI01.pdf
%V 2174 - 1.Stumme, G., Maedche, A.: Ontology Merging for Federated Ontologies for the Semantic Web. In: Franconi, E., Barker, K., and Calvanese, D. (eds.) Proc. Intl. Workshop on Foundations of Models for Information Integration (FMII’01) (2001).
@inproceedings{stumme01ontology,
author = {Stumme, G. and Maedche, A.},
booktitle = {Proc. Intl. Workshop on Foundations of Models for Information Integration (FMII'01)},
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%A Maedche, A.
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%U https://www.kde.cs.uni-kassel.de/stumme/papers/2001/FMII01.pdf - 1.Hereth, J., Stumme, G.: Reverse Pivoting in Conceptual Information Systems. In: Delugach, H. and Stumme, G. (eds.) Conceptual Structures: Broadening the Base. pp. 202–215. Springer, Heidelberg (2001).
@inproceedings{hereth01reverse,
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%U https://www.kde.cs.uni-kassel.de/stumme/papers/2001/ICCS01.pdf
%V 2120 - 1.Stumme, G., Maedche, A.: {FCA}-{M}erge: Bottom-Up Merging of Ontologies. In: Nebel, B. (ed.) Proc. 17th Intl. Conf. on Artificial Intelligence (IJCAI ’01). pp. 225–230. , Seattle, WA, USA (2001).
@inproceedings{stumme01bottom,
address = {Seattle, WA, USA},
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booktitle = {Proc. 17th Intl. Conf. on Artificial Intelligence (IJCAI '01)},
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%T {FCA}-{M}erge: Bottom-Up Merging of Ontologies.
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2001/IJCAI01.pdf - 1.Hotho, A., Maedche, A., Staab, S.: Ontology-based Text Clustering. In: Proc. of the Workshop ``Text Learning: Beyond Supervision’’ at IJCAI 2001. Seattle, WA, USA, August 6, 2001 (2001).
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booktitle = {Proc. of the Workshop ``Text Learning: Beyond Supervision'' at IJCAI 2001. Seattle, WA, USA, August 6, 2001},
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title = {Ontology-based Text Clustering},
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}%0 Conference Paper
%1 hotho-ijcaiws2001
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%A Maedche, Alexander
%A Staab, Steffen
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%D 2001
%T Ontology-based Text Clustering - 1.Hotho, A., Maedche, A., Staab, S.: Text Clustering Based on Good Aggregations. In: ICDM ’01: Proceedings of the 2001 IEEE International Conference on Data Mining. pp. 607–608. IEEE Computer Society, Washington, DC, USA (2001).
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author = {Hotho, Andreas and Maedche, Alexander and Staab, Steffen},
booktitle = {ICDM '01: Proceedings of the 2001 IEEE International Conference on Data Mining},
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%T Text Clustering Based on Good Aggregations
%U http://portal.acm.org/citation.cfm?id=658040
%@ 0-7695-1119-8 - 1.Hotho, A.: Analyse von {W}ettbewerbsverlusten im {T}elekommunikationsmarkt und mögliche {G}egenmaßnahmen. AIFB (2001).
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%T Analyse von {W}ettbewerbsverlusten im {T}elekommunikationsmarkt und mögliche {G}egenmaßnahmen - 1.Delugach, H., Stumme, G. eds.: Conceptual Structures -- Broadening the Base. Proc. 9th International Conference on Conceptual Structures. Springer, Heidelberg (2001).
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%V 2120 - 1.Stumme, G., Maedche, A., Staab, S. eds.: Ontologies. CEUR Proceedings, Aachen (2001).
@proceedings{stumme01ontologies,
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%U http://ceur-ws.org/Vol-48 - 1.Hotho, A., Maedche, A., Staab, S., Studer, R.: {SEAL-II} --- The Soft Spot between Richly Structured and Unstructured Knowledge. Journal of Universal Computer Science (J.UCS). 7, 566–590 (2001).
@article{hotho_jucs01,
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%T {SEAL-II} --- The Soft Spot between Richly Structured and Unstructured Knowledge
%V 7 - 1.Stumme, G., Hotho, A., Berendt, B. eds.: Semantic Web Mining. Workshop at 12th Europ. Conf. on Machine Learning (ECML’01) / 5th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’01), Freiburg (2001).
@proceedings{stumme_semwebmine_ws01,
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%T Semantic Web Mining - 1.Stumme, G., Hotho, A., Berendt, B. eds.: Semantic Web Mining. Workshop Proceedings. , Freiburg (2001).
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%E Stumme, G.
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%U http://semwebmine2001.aifb.uni-karlsruhe.de/online.html - 1.Schmitz, C.: {U}ntersuchung der {G}raphstruktur von {W}eb-{C}ommunities am {B}eispiel der {I}nformatik, https://www.kde.cs.uni-kassel.de/schmitz/publ/da_schmitz.pdf, (2001).
@mastersthesis{schmitz2001untersuchung,
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%U https://www.kde.cs.uni-kassel.de/schmitz/publ/da_schmitz.pdf - 1.Stumme, G., Taouil, R., Bastide, Y., Lakhal, L.: Conceptual Clustering with Iceberg Concept Lattices. In: Klinkenberg, R., Rüping, S., Fick, A., Henze, N., Herzog, C., Molitor, R., and Schröder, O. (eds.) Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML’01). , Universität Dortmund 763 (2001).
@inproceedings{stumme01conceptualclustering,
address = {Universität Dortmund 763},
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Lakhal, L.},
booktitle = {Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)},
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%1 stumme01conceptualclustering
%A Stumme, G.
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%U https://www.kde.cs.uni-kassel.de/stumme/papers/2001/FGML01.pdf - 1.Schnurr, H.P., Staab, S., Studer, R., Stumme, G., Sure, Y. eds.: Professionelles Wissensmanagement -- Erfahrungen und Visionen. Proc. WM ’01. Shaker, Aachen (2001).
@proceedings{schnurr01professionnelles,
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%T Professionelles Wissensmanagement -- Erfahrungen und Visionen. Proc. WM '01
%U http://wm2001.aifb.uni-karlsruhe.de/
2000
- 1.Staab, S., Angele, J., Decker, S., Hotho, A., Maedche, A., Schnurr, H.-P., Studer, R., Sure, Y.: AI for the Web - Ontology-based Community Web Portals. In: AAAI 2000/IAAI 2000 - Proceedings of the 17th National Conference on Artificial Intelligence and 12th Innovative Applications of Artificial Intelligence Conference, Austin/TX, USA, July 30-August 3, 2000. AAAI Press/MIT Press (2000).
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author = {Staab, Steffen and Angele, J{ü}rgen and Decker, Stefan and Hotho, Andreas and Maedche, Alexander and Schnurr, Hans-Peter and Studer, Rudi and Sure, York},
booktitle = {AAAI 2000/IAAI 2000 - Proceedings of the 17th National Conference on Artificial Intelligence and 12th Innovative Applications of Artificial Intelligence Conference, Austin/TX, USA, July 30-August 3, 2000},
keywords = {ontology},
publisher = {AAAI Press/MIT Press},
title = {AI for the Web - Ontology-based Community Web Portals},
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%1 Staab00AI
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%A Angele, J{ü}rgen
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%A Schnurr, Hans-Peter
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%B AAAI 2000/IAAI 2000 - Proceedings of the 17th National Conference on Artificial Intelligence and 12th Innovative Applications of Artificial Intelligence Conference, Austin/TX, USA, July 30-August 3, 2000
%D 2000
%I AAAI Press/MIT Press
%T AI for the Web - Ontology-based Community Web Portals
%U http://www.aifb.uni-karlsruhe.de/WBS/Publ/2000/iaai_sstetal_2000.pdf - 1.Bastide, Y., Pasquier, N., Taouil, R., Stumme, G., Lakhal, L.: Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets. In: Lloyd, J., Dahl, V., Furbach, U., Kerber, M., Laus, K.-K., Palamidessi, C., Pereira, L., Sagiv, Y., and Stuckey, P. (eds.) Computational Logic --- CL 2000 Proc. CL’00. Springer, Heidelberg (2000).
@inproceedings{bastide00miningminimal,
address = {Heidelberg},
author = {Bastide, Y. and Pasquier, N. and Taouil, R. and Stumme, G. and Lakhal, L.},
booktitle = {Computational Logic --- CL 2000 Proc. CL'00},
editor = {Lloyd, J. and Dahl, V. and Furbach, U. and Kerber, M. and Laus, K.-K. and Palamidessi, C. and Pereira, L.M. and Sagiv, Y. and Stuckey, P.J.},
keywords = {itemsets},
publisher = {Springer},
series = {LNAI},
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}%0 Conference Paper
%1 bastide00miningminimal
%A Bastide, Y.
%A Pasquier, N.
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%T Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/DOOD00.pdf
%V 1861 - 1.Stumme, G., Taouil, R., Bastide, Y., Pasquier, N., Lakhal, L.: Fast computation of concept lattices using data mining techniques. In: Proc. 7th Intl. Workshop on Knowledge Representation Meets Databases. CEUR-Workshop Proceeding., Berlin (2000).
@inproceedings{Stum00fast,
address = {Berlin},
author = {Stumme, G. and Taouil, R. and Bastide, Y. and Pasquier, N. and Lakhal, L.},
booktitle = {Proc. 7th Intl. Workshop on Knowledge Representation Meets Databases},
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month = {21--22.August},
note = {{http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/}},
publisher = {CEUR-Workshop Proceeding.},
title = {Fast computation of concept lattices using data mining techniques.},
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}%0 Conference Paper
%1 Stum00fast
%A Stumme, G.
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%A Lakhal, L.
%B Proc. 7th Intl. Workshop on Knowledge Representation Meets Databases
%C Berlin
%D 2000
%I CEUR-Workshop Proceeding.
%T Fast computation of concept lattices using data mining techniques. - 1.Bastide, Y., Taouil, R., Pasquier, N., Stumme, G., Lakhal, L.: Levelwise Search of Frequent Patterns. In: Actes des 16ièmes Journées Bases de Données Avancées. pp. 307–322. Blois, France (2000).
@inproceedings{bastide00levelwise,
address = {France},
author = {Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.},
booktitle = {Actes des 16ièmes Journées Bases de Données Avancées},
keywords = {algorithm},
month = 10,
pages = {307-322},
publisher = {Blois},
title = {Levelwise Search of Frequent Patterns},
year = 2000
}%0 Conference Paper
%1 bastide00levelwise
%A Bastide, Y.
%A Taouil, R.
%A Pasquier, N.
%A Stumme, G.
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%C France
%D 2000
%I Blois
%P 307-322
%T Levelwise Search of Frequent Patterns
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/BDA00.pdf - 1.Maedche, A., Hotho, A., Wiese, M.: Enhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing. In: Data Warehousing and Knowledge Discovery, Second International Conference, DaWaK 2000, London, UK. pp. 258–264. Springer (2000).
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author = {Maedche, Alexander and Hotho, Andreas and Wiese, Markus},
booktitle = {Data Warehousing and Knowledge Discovery, Second International Conference, DaWaK 2000, London, UK},
keywords = {intensive},
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publisher = {Springer},
series = {LNCS},
title = {Enhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing},
volume = 1874,
year = 2000
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%1 maedche_dawak00
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%A Hotho, Andreas
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%B Data Warehousing and Knowledge Discovery, Second International Conference, DaWaK 2000, London, UK
%D 2000
%I Springer
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%T Enhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing
%V 1874 - 1.Adamczak, W., Begemann, H., Stefani, S.: Research Report Online as Portal to a Wider CRIS, http://www.svenstefani.de/publ/cris2000/adamczak_fulltext.pdf, (2000).
@misc{cris2000ss,
address = {CRIS 2000, Helsinki, Finnland},
author = {Adamczak, Wolfgang and Begemann, Heinz and Stefani, Sven},
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address = {Aachen},
author = {Stumme, G. and Studer, R. and Sure, Y.},
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title = {Towards an Order-Theoretical Foundation for Maintaining and Merging Ontologies},
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%1 stumme00towardsanorder
%A Stumme, G.
%A Studer, R.
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%C Aachen
%D 2000
%E Bodendorf, F.
%E Grauer, M.
%I Shaker
%P 136-149
%T Towards an Order-Theoretical Foundation for Maintaining and Merging Ontologies
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address = {Heidelberg},
author = {Hereth, J. and Stumme, G. and Wille, R. and Wille, U.},
booktitle = {Conceptual Structures: Logical, Linguistic, and Computational Issues. Proc. ICCS '00},
editor = {Ganter, B. and Mineau, G. W.},
keywords = {knowledge},
pages = {421-437},
publisher = {Springer},
series = {LNAI},
title = {Conceptual Knowledge Discovery and Data Analysis},
volume = 1867,
year = 2000
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%A Hereth, J.
%A Stumme, G.
%A Wille, R.
%A Wille, U.
%B Conceptual Structures: Logical, Linguistic, and Computational Issues. Proc. ICCS '00
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%D 2000
%E Ganter, B.
%E Mineau, G. W.
%I Springer
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%T Conceptual Knowledge Discovery and Data Analysis
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%V 1867 - 1.Bastide, Y., Taouil, R., Pasquier, N., Stumme, G., Lakhal, L.: Mining Frequent Patterns with Counting Inference. SIGKDD Explorations, Special Issue on Scalable Algorithms. 2, 71–80 (2000).
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author = {Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.},
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number = 2,
pages = {71-80},
title = {Mining Frequent Patterns with Counting Inference.},
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%1 bastide00miningfrequent
%A Bastide, Y.
%A Taouil, R.
%A Pasquier, N.
%A Stumme, G.
%A Lakhal, L.
%D 2000
%J SIGKDD Explorations, Special Issue on Scalable Algorithms
%N 2
%P 71-80
%T Mining Frequent Patterns with Counting Inference.
%V 2 - 1.Cole, R., Eklund, P., Stumme, G.: {CEM} -- A Program for Visualization and Discovery in Email. In: Zighed, D., Komorowski, J., and Zytkow, J. (eds.) Principles of Data Mining and Knowledge Discovery. Proc. PKDD 2000. pp. 367–374. Springer, Heidelberg-Berlin (2000).
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booktitle = {Principles of Data Mining and Knowledge Discovery. Proc. PKDD 2000},
editor = {Zighed, D.A. and Komorowski, J. and Zytkow, J.},
keywords = {analysis},
pages = {367-374},
publisher = {Springer},
series = {LNAI},
title = {{CEM} -- A Program for Visualization and Discovery in Email},
volume = 1910,
year = 2000
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%1 cole00program
%A Cole, R.
%A Eklund, P.
%A Stumme, G.
%B Principles of Data Mining and Knowledge Discovery. Proc. PKDD 2000
%C Heidelberg-Berlin
%D 2000
%E Zighed, D.A.
%E Komorowski, J.
%E Zytkow, J.
%I Springer
%P 367-374
%T {CEM} -- A Program for Visualization and Discovery in Email
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/PKDD00.pdf
%V 1910 - 1.Hotho, A.: Analyse von {W}ettbewerbsverlusten im {T}elekommunikationsmarkt und mögliche {G}egenmaßnahmen. AIFB (2000).
@techreport{hotho_telekom99,
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title = {Analyse von {W}ettbewerbsverlusten im {T}elekommunikationsmarkt und mögliche {G}egenmaßnahmen},
type = {Projektbericht 1999 für die {D}eutsche {T}elekom {AG}},
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%T Analyse von {W}ettbewerbsverlusten im {T}elekommunikationsmarkt und mögliche {G}egenmaßnahmen - 1.Stumme, G., Wille, R. eds.: Begriffliche Wissensverarbeitung -- Methoden und Anwendungen. Springer, Heidelberg (2000).
@proceedings{stumme00begriffliche,
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%1 stumme00begriffliche
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%T Begriffliche Wissensverarbeitung -- Methoden und Anwendungen
%U http://www.springer.com/dal/home/generic/search/results?SGWID=1-40109-22-2058937-0 - 1.Göbel, S., Heidemann, M., Jasnoch, U., Stumme, G.: Einsatz von {GIS} und {F}ormaler {B}egriffsanalyse in {A}ltlasten-{I}nformationssystemen. In: Tochtermann, K. and Riekert, W.-F. (eds.) Hypermedia im Umweltschutz. 3. Workshop in Ulm 2000. pp. 169–179. , Marburg (2000).
@inproceedings{goebel00einsatz,
address = {Marburg},
author = {Göbel, S. and Heidemann, M. and Jasnoch, U. and Stumme, G.},
booktitle = {Hypermedia im Umweltschutz. 3. Workshop in Ulm 2000},
editor = {Tochtermann, K. and Riekert, W.-F.},
keywords = {altlasten},
pages = {169-179},
title = {Einsatz von {GIS} und {F}ormaler {B}egriffsanalyse in {A}ltlasten-{I}nformationssystemen},
volume = {Umwelt-Informatik aktuell, Bd. 24},
year = 2000
}%0 Conference Paper
%1 goebel00einsatz
%A Göbel, S.
%A Heidemann, M.
%A Jasnoch, U.
%A Stumme, G.
%B Hypermedia im Umweltschutz. 3. Workshop in Ulm 2000
%C Marburg
%D 2000
%E Tochtermann, K.
%E Riekert, W.-F.
%P 169-179
%T Einsatz von {GIS} und {F}ormaler {B}egriffsanalyse in {A}ltlasten-{I}nformationssystemen
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/AKHU00.pdf
%V Umwelt-Informatik aktuell, Bd. 24 - 1.Cole, R., Stumme, G.: {CEM} - A Conceptual Email Manager. In: Ganter, B. and Mineau, G.W. (eds.) Conceptual Structures: Logical, Linguistic, and Computational Issues. Proc. ICCS ’00. pp. 438–452. Springer, Heidelberg (2000).
@inproceedings{cole2000conceptual,
address = {Heidelberg},
author = {Cole, R. and Stumme, G.},
booktitle = {Conceptual Structures: Logical, Linguistic, and Computational Issues. Proc. ICCS '00},
editor = {Ganter, B. and Mineau, G. W.},
keywords = {analysis},
note = {{P}art of \cite{cole03document}},
pages = {438-452},
publisher = {Springer},
series = {LNAI},
title = {{CEM} - A Conceptual Email Manager},
volume = 1867,
year = 2000
}%0 Conference Paper
%1 cole2000conceptual
%A Cole, R.
%A Stumme, G.
%B Conceptual Structures: Logical, Linguistic, and Computational Issues. Proc. ICCS '00
%C Heidelberg
%D 2000
%E Ganter, B.
%E Mineau, G. W.
%I Springer
%P 438-452
%T {CEM} - A Conceptual Email Manager
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/P2088_ICCS00_emails.pdf
%V 1867 - 1.Stumme, G.: 8th {I}nternational {C}onference on {C}onceptual {S}tructures. {C}onference {R}eport. Knowledge Organization. 27, 162 (2000).
@article{stumme008thinternational,
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title = {8th {I}nternational {C}onference on {C}onceptual {S}tructures. {C}onference {R}eport},
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%T 8th {I}nternational {C}onference on {C}onceptual {S}tructures. {C}onference {R}eport
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/ConferenceReportICCS00.pdf
%V 27 - 1.Stumme, G.: Conceptual {O}n-{L}ine {A}nalytical {P}rocessing. In: Tanaka, K., Ghandeharizadeh, S., and Kambayashi, Y. (eds.) Information Organization and Databases. pp. 191–203. Kluwer, Boston-Dordrecht-London (2000).
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%T Conceptual {O}n-{L}ine {A}nalytical {P}rocessing
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/Kluwer00.ps
%& 14 - 1.Eklund, P., Groh, B., Stumme, G., Wille, R.: Contextual-Logic Extension of TOSCANA. In: Ganter, B. and Mineau, G.W. (eds.) Conceptual Structures: Logical, Linguistic, and Computational. pp. 453–467. Springer, Heidelberg (2000).
@inproceedings{eklund00contextual,
address = {Heidelberg},
author = {Eklund, P. and Groh, B. and Stumme, G. and Wille, R.},
booktitle = {Conceptual Structures: Logical, Linguistic, and Computational},
editor = {Ganter, B. and Mineau, G. W.},
keywords = {iccs},
pages = {453-467},
publisher = {Springer},
series = {LNAI},
title = {Contextual-Logic Extension of TOSCANA.},
volume = 1867,
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}%0 Conference Paper
%1 eklund00contextual
%A Eklund, P.
%A Groh, B.
%A Stumme, G.
%A Wille, R.
%B Conceptual Structures: Logical, Linguistic, and Computational
%C Heidelberg
%D 2000
%E Ganter, B.
%E Mineau, G. W.
%I Springer
%P 453-467
%T Contextual-Logic Extension of TOSCANA.
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/ICCS_toscanaextension.pdf
%V 1867 - 1.Stumme, G. ed.: Working with Conceptual Structures -- Contributions to ICCS 2000. Suppl. Proc. 8th International Conference on Conceptual Structures (ICCS 2000). Shaker, Aachen (2000).
@proceedings{stumme00working,
address = {Aachen},
editor = {Stumme, G.},
keywords = {proceedings},
publisher = {Shaker},
title = {Working with Conceptual Structures -- Contributions to ICCS 2000. Suppl. Proc. 8th International Conference on Conceptual Structures (ICCS 2000)},
year = 2000
}%0 Conference Proceedings
%1 stumme00working
%C Aachen
%D 2000
%E Stumme, G.
%I Shaker
%T Working with Conceptual Structures -- Contributions to ICCS 2000. Suppl. Proc. 8th International Conference on Conceptual Structures (ICCS 2000) - 1.Stumme, G.: Begriffliche Wissensverarbeitung -- Methoden und Anwendungen. Springer, Heidelberg (2000).
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%T Begriffliche Wissensverarbeitung -- Methoden und Anwendungen - 1.Becker, K., Stumme, G., Wille, R., Wille, U., Zickwolff, M.: Conceptual Information Systems Discussed Through an {IT}-Security Tool. In: Dieng, R. and Corby, O. (eds.) Knowledge Engineering and Knowledge Management. Methods, Models, and Tools. pp. 352–365. Springer, Heidelberg (2000).
@inproceedings{becker00conceptual,
address = {Heidelberg},
author = {Becker, K. and Stumme, G. and Wille, R. and Wille, U. and Zickwolff, M.},
booktitle = {Knowledge Engineering and Knowledge Management. Methods, Models, and Tools.},
editor = {Dieng, R. and Corby, O.},
keywords = {lattices},
pages = {352-365},
publisher = {Springer},
series = {LNAI},
title = {Conceptual Information Systems Discussed Through an {IT}-Security Tool},
volume = 1937,
year = 2000
}%0 Conference Paper
%1 becker00conceptual
%A Becker, K.
%A Stumme, G.
%A Wille, R.
%A Wille, U.
%A Zickwolff, M.
%B Knowledge Engineering and Knowledge Management. Methods, Models, and Tools.
%C Heidelberg
%D 2000
%E Dieng, R.
%E Corby, O.
%I Springer
%P 352-365
%T Conceptual Information Systems Discussed Through an {IT}-Security Tool
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/EKAW00.pdf
%V 1937 - 1.Staab, S., Angele, J., Decker, S., Erdmann, M., Hotho, A., Maedche, A., Schnurr, H.-P., Studer, R., Sure, Y.: Semantic Community Web Portals. In: WWW9 --- Proceedings of the 9th International World Wide Web Conference, Amsterdam, The Netherlands. pp. 473–491. Elsevier (2000).
@inproceedings{staab.www9,
author = {Staab, S. and Angele, J. and Decker, S. and Erdmann, M. and Hotho, A. and Maedche, A. and Schnurr, H.-P. and Studer, R. and Sure, Y.},
booktitle = {WWW9 --- Proceedings of the 9th International World Wide Web Conference, Amsterdam, The Netherlands},
keywords = {community},
pages = {473-491},
publisher = {Elsevier},
title = {Semantic Community Web Portals},
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}%0 Conference Paper
%1 staab.www9
%A Staab, S.
%A Angele, J.
%A Decker, S.
%A Erdmann, M.
%A Hotho, A.
%A Maedche, A.
%A Schnurr, H.-P.
%A Studer, R.
%A Sure, Y.
%B WWW9 --- Proceedings of the 9th International World Wide Web Conference, Amsterdam, The Netherlands
%D 2000
%I Elsevier
%P 473-491
%T Semantic Community Web Portals
1999
- 1.Mineau, G., Stumme, G., Wille, R.: Conceptual Structures Represented by Conceptual Graphs and Formal Concept Analysis. In: Tepfenhart, W. and Cyre, W. (eds.) Conceptual Structures: Standards and Practices. Proc. ICCS ’99. pp. 423–441. Springer, Heidelberg (1999).
@inproceedings{mineau99conceptual,
address = {Heidelberg},
author = {Mineau, Guy and Stumme, Gerd and Wille, Rudolf},
booktitle = {Conceptual Structures: Standards and Practices. Proc. ICCS '99},
editor = {Tepfenhart, W. and Cyre, W.},
keywords = {knowledge},
pages = {423-441},
publisher = {Springer},
series = {LNAI},
title = {Conceptual Structures Represented by Conceptual Graphs and Formal Concept Analysis},
volume = 1640,
year = 1999
}%0 Conference Paper
%1 mineau99conceptual
%A Mineau, Guy
%A Stumme, Gerd
%A Wille, Rudolf
%B Conceptual Structures: Standards and Practices. Proc. ICCS '99
%C Heidelberg
%D 1999
%E Tepfenhart, W.
%E Cyre, W.
%I Springer
%P 423-441
%T Conceptual Structures Represented by Conceptual Graphs and Formal Concept Analysis
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1999/ICCS99.pdf
%V 1640 - 1.Stumme, G.: Acquiring Expert Knowledge for the Design of Conceptual Information Systems. In: Fensel, D. and Studer, R. (eds.) Knowledge Acquisition, Modeling, and Management. Proc. 11th European. pp. 275–290. Springer, Heidelberg (1999).
@inproceedings{Stumme1999acquiring,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {Knowledge Acquisition, Modeling, and Management. Proc. 11th European},
editor = {Fensel, D. and Studer, R.},
keywords = {lattices},
pages = {275-290},
publisher = {Springer},
series = {LNAI},
title = {Acquiring Expert Knowledge for the Design of Conceptual Information Systems},
volume = 1621,
year = 1999
}%0 Conference Paper
%1 Stumme1999acquiring
%A Stumme, Gerd
%B Knowledge Acquisition, Modeling, and Management. Proc. 11th European
%C Heidelberg
%D 1999
%E Fensel, D.
%E Studer, R.
%I Springer
%P 275-290
%T Acquiring Expert Knowledge for the Design of Conceptual Information Systems
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1999/P1997-EKAW99.pdf
%V 1621 - 1.Stumme, G.: Conceptual Knowledge Discovery with Frequent Concept Lattices. TU Darmstadt (1999).
@techreport{stumme99conceptualknowledge,
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%T Conceptual Knowledge Discovery with Frequent Concept Lattices
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1999/P2043.pdf - 1.Prediger, S., Stumme, G.: Theory-Driven Logical Scaling. In: et al, E.F. (ed.) Proc. 6th Intl. Workshop Knowledge Representation Meets Databases (KRDB’99) (1999).
@inproceedings{prediger99theory,
author = {Prediger, S. and Stumme, G.},
booktitle = {Proc. 6th Intl. Workshop Knowledge Representation Meets Databases (KRDB'99)},
editor = {et al, E. Franconi},
keywords = {lattices},
note = {Also in: P. Lambrix et al (Eds.): Proc. Intl. Workshop on Description Logics (DL'99). CEUR Workshop Proc. 22, 1999 \url{http://ceur-ws.org/Vol-21}},
title = {Theory-Driven Logical Scaling},
volume = {CEUR Workshop Proc. 21},
year = 1999
}%0 Conference Paper
%1 prediger99theory
%A Prediger, S.
%A Stumme, G.
%B Proc. 6th Intl. Workshop Knowledge Representation Meets Databases (KRDB'99)
%D 1999
%E et al, E. Franconi
%T Theory-Driven Logical Scaling
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1999/KRDB99.pdf
%V CEUR Workshop Proc. 21 - 1.Stumme, G.: Dual Retrieval in Conceptual Information Systems. In: Buchmann, A. (ed.) Datenbanksysteme in Büro, Technik und Wissenschaft. Proc. BTW’99. pp. 328–342. , Heidelberg (1999).
@inproceedings{stumme99dual,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {Datenbanksysteme in Büro, Technik und Wissenschaft. Proc. BTW'99},
editor = {Buchmann, A.},
keywords = {information},
pages = {328-342},
title = {Dual Retrieval in Conceptual Information Systems},
year = 1999
}%0 Conference Paper
%1 stumme99dual
%A Stumme, Gerd
%B Datenbanksysteme in Büro, Technik und Wissenschaft. Proc. BTW'99
%C Heidelberg
%D 1999
%E Buchmann, A.
%P 328-342
%T Dual Retrieval in Conceptual Information Systems
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1999/P2021-BTW99.pdf - 1.Skorsky, M., Stumme, G., Wille, R., Wille, U.: Reuse in the Development Process of {TOSCANA} Systems. In: Puppe, F., Fensel, D., Kühler, J., Studer, R., and Wetter, T. (eds.) Proc. Workshop on Knowledge Management, Organizational Memory and Reuse, 5th German Conf. on. , Würzburg (1999).
@inproceedings{skorsky1999reuse,
address = {Würzburg},
author = {Skorsky, M. and Stumme, G. and Wille, R. and Wille, U.},
booktitle = {Proc. Workshop on Knowledge Management, Organizational Memory and Reuse, 5th German Conf. on},
editor = {Puppe, F. and Fensel, D. and Kühler, J. and Studer, R. and Wetter, Th.},
keywords = {analysis},
month = {03},
title = {Reuse in the Development Process of {TOSCANA} Systems},
year = 1999
}%0 Conference Paper
%1 skorsky1999reuse
%A Skorsky, M.
%A Stumme, G.
%A Wille, R.
%A Wille, U.
%B Proc. Workshop on Knowledge Management, Organizational Memory and Reuse, 5th German Conf. on
%C Würzburg
%D 1999
%E Puppe, F.
%E Fensel, D.
%E Kühler, J.
%E Studer, R.
%E Wetter, Th.
%T Reuse in the Development Process of {TOSCANA} Systems
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1999/XPS99.pdf - 1.Stumme, G.: Hierarchies of Conceptual Scales. In: Gaines, T.B., Kremer, R., and Musen, M. (eds.) Proc.Workshop on Knowledge Acquisition, Modeling and Management (KAW’99). pp. 78–95. Banff (1999).
@inproceedings{stumme99hierarchies,
author = {Stumme, G.},
booktitle = {Proc.Workshop on Knowledge Acquisition, Modeling and Management (KAW'99)},
editor = {Gaines, T. B. and Kremer, R. and Musen, M.},
keywords = {ontologies},
month = 10,
pages = {78-95},
publisher = {Banff},
title = {Hierarchies of Conceptual Scales},
volume = 2,
year = 1999
}%0 Conference Paper
%1 stumme99hierarchies
%A Stumme, G.
%B Proc.Workshop on Knowledge Acquisition, Modeling and Management (KAW'99)
%D 1999
%E Gaines, T. B.
%E Kremer, R.
%E Musen, M.
%I Banff
%P 78-95
%T Hierarchies of Conceptual Scales
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1999/KAW99.pdf
%V 2 - 1.Stumme, G., Wolff, K.E.: Numerical Aspects in the Data Model of Conceptual Information Systems. In: Kambayashi, Y., Lee, D.K., Lim, E.-P., Mohania, M.K., and Masunaga, Y. (eds.) Advances in Database Technologies. Proc. Intl. Workshop on Data Warehousing and. pp. 117–128. Springer, Heidelberg (1999).
@inproceedings{stumme99numerical,
address = {Heidelberg},
author = {Stumme, G. and Wolff, K. E.},
booktitle = {Advances in Database Technologies. Proc. Intl. Workshop on Data Warehousing and},
editor = {Kambayashi, Y. and Lee, Dik Kun and Lim, Ee-Peng and Mohania, M. K. and Masunaga, Y.},
keywords = {numerical},
pages = {117-128},
publisher = {Springer},
series = {LNCS},
title = {Numerical Aspects in the Data Model of Conceptual Information Systems},
volume = 1552,
year = 1999
}%0 Conference Paper
%1 stumme99numerical
%A Stumme, G.
%A Wolff, K. E.
%B Advances in Database Technologies. Proc. Intl. Workshop on Data Warehousing and
%C Heidelberg
%D 1999
%E Kambayashi, Y.
%E Lee, Dik Kun
%E Lim, Ee-Peng
%E Mohania, M. K.
%E Masunaga, Y.
%I Springer
%P 117-128
%T Numerical Aspects in the Data Model of Conceptual Information Systems
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1998/ER98.pdf
%V 1552
1998
- 1.Stumme, G.: On-Line Analytical Processing with Conceptual Information Systems. In: Tanaka, K. and Ghandeharizadeh, S. (eds.) Proc. 5th Intl. Conf. on Foundations of Data Organization (FODO’98). pp. 117–126 (1998).
@inproceedings{stumme98online,
author = {Stumme, Gerd},
booktitle = {Proc. 5th Intl. Conf. on Foundations of Data Organization (FODO'98)},
editor = {Tanaka, K. and Ghandeharizadeh, S.},
keywords = {olap},
month = 11,
note = {Short version of \cite{stumme00conceptual}},
pages = {117-126},
title = {On-Line Analytical Processing with Conceptual Information Systems},
year = 1998
}%0 Conference Paper
%1 stumme98online
%A Stumme, Gerd
%B Proc. 5th Intl. Conf. on Foundations of Data Organization (FODO'98)
%D 1998
%E Tanaka, K.
%E Ghandeharizadeh, S.
%P 117-126
%T On-Line Analytical Processing with Conceptual Information Systems
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1998/FODO98.pdf - 1.Stumme, G.: Exploring Conceptual Similarities of Objects for Analyzing Inconsistencies in Relational Databases. In: Bing, L., Hsu, W., and Ke, W. (eds.) Proc.Workshop on Knowledge Discovery and Data Mining, 5th Pacific Rim Intl. Conf. on Artificial. pp. 41–50. , Singapore (1998).
@inproceedings{stummeexploring98,
address = {Singapore},
author = {Stumme, Gerd},
booktitle = {Proc.Workshop on Knowledge Discovery and Data Mining, 5th Pacific Rim Intl. Conf. on Artificial},
editor = {Bing, L. and Hsu, W. and Ke, W.},
keywords = {databases},
month = 11,
pages = {41-50},
title = {Exploring Conceptual Similarities of Objects for Analyzing Inconsistencies in Relational Databases.},
year = 1998
}%0 Conference Paper
%1 stummeexploring98
%A Stumme, Gerd
%B Proc.Workshop on Knowledge Discovery and Data Mining, 5th Pacific Rim Intl. Conf. on Artificial
%C Singapore
%D 1998
%E Bing, L.
%E Hsu, W.
%E Ke, W.
%P 41-50
%T Exploring Conceptual Similarities of Objects for Analyzing Inconsistencies in Relational Databases.
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1998/P2020-PRICAI98.pdf - 1.Stumme, G., Wille, R., Wille, U.: Conceptual Knowledge Discovery in Databases Using Formal Concept Analysis Methods. In: Zytkow, J.M. and Quafofou, M. (eds.) Principles of Data Mining and Knowledge Discovery Proc. 2nd European Symposium on PKDD’98. pp. 450–458. , Heidelberg (1998).
@inproceedings{stumme98conceptual,
address = {Heidelberg},
author = {Stumme, Gerd and Wille, Rudolf and Wille, Uta},
booktitle = {Principles of Data Mining and Knowledge Discovery Proc. 2nd European Symposium on PKDD'98},
editor = {Zytkow, J. M. and Quafofou, M.},
keywords = {databases},
note = {{P}art of \cite{hereth03conceptual}},
pages = {450-458},
series = {LNAI},
title = {Conceptual Knowledge Discovery in Databases Using Formal Concept Analysis Methods},
volume = 1510,
year = 1998
}%0 Conference Paper
%1 stumme98conceptual
%A Stumme, Gerd
%A Wille, Rudolf
%A Wille, Uta
%B Principles of Data Mining and Knowledge Discovery Proc. 2nd European Symposium on PKDD'98
%C Heidelberg
%D 1998
%E Zytkow, J. M.
%E Quafofou, M.
%P 450-458
%T Conceptual Knowledge Discovery in Databases Using Formal Concept Analysis Methods
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1998/P1993-PKDD98.pdf
%V 1510 - 1.Stumme, G.: Distributive Concept Exploration - A Knowledge Acquisition Tool in Formal Concept Analysis. In: Herzog, O. and Günter, A. (eds.) KI-98: Advances in Artificial Intelligence. Proc. 22. Jahrestagung. pp. 117–128. Springer, Heidelberg (1998).
@inproceedings{stumme98knowledgeacquisition,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {KI-98: Advances in Artificial Intelligence. Proc. 22. Jahrestagung},
editor = {Herzog, O. and Günter, A.},
keywords = {knowledge},
pages = {117-128},
publisher = {Springer},
series = {LNAI},
title = {Distributive Concept Exploration - A Knowledge Acquisition Tool in Formal Concept Analysis},
volume = 1504,
year = 1998
}%0 Conference Paper
%1 stumme98knowledgeacquisition
%A Stumme, Gerd
%B KI-98: Advances in Artificial Intelligence. Proc. 22. Jahrestagung
%C Heidelberg
%D 1998
%E Herzog, O.
%E Günter, A.
%I Springer
%P 117-128
%T Distributive Concept Exploration - A Knowledge Acquisition Tool in Formal Concept Analysis
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1998/KI98.pdf
%V 1504 - 1.Stumme, G.: Free Distributive Completions of Partial Complete Lattices. {In:} {O}rder. 14, 179–189 (1998).
@article{stumme98free,
author = {Stumme, Gerd},
journal = {{In:} {O}rder},
keywords = {theory},
pages = {179-189},
title = {Free Distributive Completions of Partial Complete Lattices},
volume = 14,
year = 1998
}%0 Journal Article
%1 stumme98free
%A Stumme, Gerd
%D 1998
%J {In:} {O}rder
%P 179-189
%T Free Distributive Completions of Partial Complete Lattices
%U https://www.kde.cs.uni-kassel.de/stumme/papers/2000/SIGKDD_Explorations00.ps
%V 14 - 1.Stumme, G.: Knowledge, {L}ogic, {I}nformation. {C}onference {R}eport. Zeitschrift für Semiotik. 20, 424 (1998).
@article{stumme98knowledge,
author = {Stumme, Gerd},
journal = {Zeitschrift für Semiotik},
keywords = {report},
number = {3-4},
pages = 424,
title = {Knowledge, {L}ogic, {I}nformation. {C}onference {R}eport.},
volume = 20,
year = 1998
}%0 Journal Article
%1 stumme98knowledge
%A Stumme, Gerd
%D 1998
%J Zeitschrift für Semiotik
%N 3-4
%P 424
%T Knowledge, {L}ogic, {I}nformation. {C}onference {R}eport.
%V 20
1997
- 1.Stumme, G.: Concept Exploration - A Tool for Creating and Exploring Conceptual Hierarchies. In: Lukose, D., Delugach, H., Keeler, M., Searle, L., and Sowa, J.F. (eds.) Conceptual Structures: Fulfilling Peirce’s Dream. Proc. ICCS’97. Springer, Berlin (1997).
@inproceedings{stumme97tool,
address = {Berlin},
author = {Stumme, Gerd},
booktitle = {Conceptual Structures: Fulfilling Peirce's Dream. Proc. ICCS'97},
editor = {Lukose, D. and Delugach, H. and Keeler, M. and Searle, L. and Sowa, J. F.},
keywords = {Conceptual},
publisher = {Springer},
series = {LNAI},
title = {Concept Exploration - A Tool for Creating and Exploring Conceptual Hierarchies},
volume = 1257,
year = 1997
}%0 Conference Paper
%1 stumme97tool
%A Stumme, Gerd
%B Conceptual Structures: Fulfilling Peirce's Dream. Proc. ICCS'97
%C Berlin
%D 1997
%E Lukose, D.
%E Delugach, H.
%E Keeler, M.
%E Searle, L.
%E Sowa, J. F.
%I Springer
%T Concept Exploration - A Tool for Creating and Exploring Conceptual Hierarchies
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1997/P1905-ICCS97.pdf
%V 1257 - 1.Stumme, G., Wolff, K.E.: Computing in Conceptual Data systems with relational structures. In: Proc. Intl. Symposium on Knowledge Retrieval, Use, and Storage for Efficiency. pp. 206–219. , Vancouver, Canada (1997).
@inproceedings{stumme97computing,
address = {Vancouver, Canada},
author = {Stumme, Gerd and Wolff, Karl Erich},
booktitle = {Proc. Intl. Symposium on Knowledge Retrieval, Use, and Storage for Efficiency},
keywords = {lattices},
month = {08},
pages = {206-219},
title = {Computing in Conceptual Data systems with relational structures},
year = 1997
}%0 Conference Paper
%1 stumme97computing
%A Stumme, Gerd
%A Wolff, Karl Erich
%B Proc. Intl. Symposium on Knowledge Retrieval, Use, and Storage for Efficiency
%C Vancouver, Canada
%D 1997
%P 206-219
%T Computing in Conceptual Data systems with relational structures
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1997/KRUSE97.pdf - 1.Stumme, G.: Concept Exploration -- Knowledge Acquisition in Knowledge Systems. Shaker, Aachen (1997).
@book{stumme97conceptexploration,
address = {Aachen},
author = {Stumme, Gerd},
keywords = {knowledge},
publisher = {Shaker},
title = {Concept Exploration -- Knowledge Acquisition in Knowledge Systems.},
year = 1997
}%0 Book
%1 stumme97conceptexploration
%A Stumme, Gerd
%C Aachen
%D 1997
%I Shaker
%T Concept Exploration -- Knowledge Acquisition in Knowledge Systems.
%U http://www.shaker.de/Online-Gesamtkatalog/details.asp?ISBN=3-8265-2930-8
1996
- 1.Stumme, G.: Attribute Exploration with Background Implications and Exceptions. In: Bock, H.-H. and Polasek, W. (eds.) Data Analysis and Information Systems. Statistical and Conceptual approaches. Proc. GfKl’95. Studies in Classification, Data Analysis, and Knowledge Organization 7. pp. 457–469. Springer, Heidelberg (1996).
@inproceedings{stumme96attribute,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {Data Analysis and Information Systems. Statistical and Conceptual approaches. Proc. GfKl'95. Studies in Classification, Data Analysis, and Knowledge Organization 7},
editor = {Bock, H.-H. and Polasek, W.},
keywords = {lattices},
pages = {457-469},
publisher = {Springer},
title = {Attribute Exploration with Background Implications and Exceptions},
year = 1996
}%0 Conference Paper
%1 stumme96attribute
%A Stumme, Gerd
%B Data Analysis and Information Systems. Statistical and Conceptual approaches. Proc. GfKl'95. Studies in Classification, Data Analysis, and Knowledge Organization 7
%C Heidelberg
%D 1996
%E Bock, H.-H.
%E Polasek, W.
%I Springer
%P 457-469
%T Attribute Exploration with Background Implications and Exceptions
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1995/P1781-GfKl95.pdf - 1.Stumme, G.: The Concept Classification of a Terminology Extended by Conjunction and Disjunction. In: Foo, N. and Goebel, R. (eds.) PRICAI’96: Topics in Artificial Intelligence. Proc. PRICAI’96. pp. 121–131. Springer, Heidelberg (1996).
@inproceedings{stumme96concept,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {PRICAI'96: Topics in Artificial Intelligence. Proc. PRICAI'96},
editor = {Foo, N. and Goebel, R.},
keywords = {classification},
pages = {121-131},
publisher = {Springer},
series = {LNAI},
title = {The Concept Classification of a Terminology Extended by Conjunction and Disjunction},
volume = 1114,
year = 1996
}%0 Conference Paper
%1 stumme96concept
%A Stumme, Gerd
%B PRICAI'96: Topics in Artificial Intelligence. Proc. PRICAI'96
%C Heidelberg
%D 1996
%E Foo, N.
%E Goebel, R.
%I Springer
%P 121-131
%T The Concept Classification of a Terminology Extended by Conjunction and Disjunction
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1996/P1829-PRICAI96.pdf
%V 1114 - 1.Stumme, G.: Exploration Tools in Formal Concept Analysis. In: Diday, E., Lechevallier, Y., and Opitz, O. (eds.) Ordinal and Symbolic Data Analysis. Proc. OSDA’95. Studies in Classification, Data Analysis, and Knowledge Organization 8. pp. 31–44. Springer, Heidelberg (1996).
@inproceedings{stumme96exploration,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {Ordinal and Symbolic Data Analysis. Proc. OSDA'95. Studies in Classification, Data Analysis, and Knowledge Organization 8},
editor = {Diday, E. and Lechevallier, Y. and Opitz, O.},
keywords = {lattices},
pages = {31-44},
publisher = {Springer},
title = {Exploration Tools in Formal Concept Analysis},
year = 1996
}%0 Conference Paper
%1 stumme96exploration
%A Stumme, Gerd
%B Ordinal and Symbolic Data Analysis. Proc. OSDA'95. Studies in Classification, Data Analysis, and Knowledge Organization 8
%C Heidelberg
%D 1996
%E Diday, E.
%E Lechevallier, Y.
%E Opitz, O.
%I Springer
%P 31-44
%T Exploration Tools in Formal Concept Analysis
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1995/P1796-OSDA95.pdf - 1.Stumme, G.: Local Scaling in Conceptual Data Systems. In: Eklund, P.W., Ellis, G., and Mann, G. (eds.) Conceptual Structures: Knowledge Representation as Interlingua Proc. ICCS’96. pp. 308–320. Springer, Heidelberg (1996).
@inproceedings{stumme96local,
address = {Heidelberg},
author = {Stumme, Gerd},
booktitle = {Conceptual Structures: Knowledge Representation as Interlingua Proc. ICCS'96},
editor = {Eklund, P. W. and Ellis, G. and Mann, G.},
keywords = {lattices},
pages = {308-320},
publisher = {Springer},
series = {LNAI},
title = {Local Scaling in Conceptual Data Systems},
volume = 1115,
year = 1996
}%0 Conference Paper
%1 stumme96local
%A Stumme, Gerd
%B Conceptual Structures: Knowledge Representation as Interlingua Proc. ICCS'96
%C Heidelberg
%D 1996
%E Eklund, P. W.
%E Ellis, G.
%E Mann, G.
%I Springer
%P 308-320
%T Local Scaling in Conceptual Data Systems
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1996/P1827-ICCS96.pdf
%V 1115 - 1.Stumme, G.: International Conference on Conceptual Knowledge Processing. Conference Report. Zeitschrift für Semiotik. 18, 381 (1996).
@article{stummei96international,
author = {Stumme, G.},
journal = {Zeitschrift für Semiotik},
keywords = {report},
number = {Heft 2-3},
pages = 381,
title = {International Conference on Conceptual Knowledge Processing. Conference Report.},
volume = 18,
year = 1996
}%0 Journal Article
%1 stummei96international
%A Stumme, G.
%D 1996
%J Zeitschrift für Semiotik
%N Heft 2-3
%P 381
%T International Conference on Conceptual Knowledge Processing. Conference Report.
%V 18
1995
- 1.Stumme, G., Wille, R.: A Geometrical Heuristic for Drawing Concept Lattices. In: Tamassia, R. and Tollis, I. (eds.) Graph Drawing. pp. 452–459. Springer, Heidelberg (1995).
@inproceedings{stumme95geometrical,
address = {Heidelberg},
author = {Stumme, Gerd and Wille, Rudolf},
booktitle = {Graph Drawing},
editor = {Tamassia, R. and Tollis, I.G.},
keywords = {graph},
pages = {452-459},
publisher = {Springer},
series = {LNCS},
title = {A Geometrical Heuristic for Drawing Concept Lattices},
volume = 894,
year = 1995
}%0 Conference Paper
%1 stumme95geometrical
%A Stumme, Gerd
%A Wille, Rudolf
%B Graph Drawing
%C Heidelberg
%D 1995
%E Tamassia, R.
%E Tollis, I.G.
%I Springer
%P 452-459
%T A Geometrical Heuristic for Drawing Concept Lattices
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1994/P1677-GD94.pdf
%V 894 - 1.Stumme, G.: Knowledge acquisition by distributive concept exploration. In: Ellis, G., Levinson, R., Rich, W., and Sowa, J.F. (eds.) Conceptual structures: applications, implementation and theory. Springer--Verlag, Berlin--Heidelberg--New~York (1995).
@inproceedings{stumme1995knowledge,
address = {Berlin--Heidelberg--New~York},
author = {Stumme, Gerd},
booktitle = {Conceptual structures: applications, implementation and theory},
editor = {Ellis, G. and Levinson, R. and Rich, W. and Sowa, J. F.},
keywords = {lattices},
number = 954,
publisher = {Springer--Verlag},
series = {Lecture Notes in Artificial Intelligence},
title = {Knowledge acquisition by distributive concept exploration},
year = 1995
}%0 Conference Paper
%1 stumme1995knowledge
%A Stumme, Gerd
%B Conceptual structures: applications, implementation and theory
%C Berlin--Heidelberg--New~York
%D 1995
%E Ellis, G.
%E Levinson, R.
%E Rich, W.
%E Sowa, J. F.
%I Springer--Verlag
%N 954
%T Knowledge acquisition by distributive concept exploration
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1995/ICCS95_not_in_cv.pdf
1994
- 1.Stumme, G.: Boolesche {B}egriffe, https://www.kde.cs.uni-kassel.de/stumme/papers/1994/Diplomarbeit94.pdf, (1994).
@mastersthesis{stumme94boolesche,
author = {Stumme, Gerd},
keywords = {lattices},
school = {TH Darmstadt},
title = {Boolesche {B}egriffe},
type = {Diplomarbeit},
year = 1994
}%0 Thesis
%1 stumme94boolesche
%A Stumme, Gerd
%D 1994
%T Boolesche {B}egriffe
%U https://www.kde.cs.uni-kassel.de/stumme/papers/1994/Diplomarbeit94.pdf