Publications
This publication list is generated automatically from BibSonomy.
Evaluation of Folksonomy Induction Algorithms.
Transactions on Intelligent Systems and Technology, 2012.
Markus Strohmaier, Denis Helic, Dominik Benz, Christian Körner and Roman Kern.
[doi]
[BibTeX]
Enhancing Social Interactions at Conferences.
it - Information Technology, 53(3):101-107, 2011.
Martin Atzmueller, Dominik Benz, Stephan Doerfel, Andreas Hotho, Robert Jäschke, Bjoern Elmar Macek, Folke Mitzlaff, Christoph Scholz and Gerd Stumme.
[doi]
[BibTeX]
Towards Mining Semantic Maturity in Social Bookmarking Systems.
In: A. Passant, S. Fernández, J. Breslin and U. Boj?rs, editors,
Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011).
2011.
Martin Atzmüller, Dominik Benz, Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
One Tag to Bind Them All : Measuring Term Abstractness in Social Metadata.
In: G. Antoniou, M. Grobelnik, E. Simperl, B. Parsia, D. Plexousakis, J. Pan and P. D. Leenheer, editors,
Proceedings of the 8th Extended Semantic Web Conference (ESWC 2011).
Heraklion, Crete, 2011.
Dominik Benz, Christian Körner, Andreas Hotho, Gerd Stumme and Markus Strohmaier.
[doi]
[abstract]
[BibTeX]
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.
Community Assessment using Evidence Networks.
In:
Analysis of Social Media and Ubiquitous Data, volume 6904, series LNAI.
2011.
Folke Mitzlaff, Martin Atzmueller, Dominik Benz, Andreas Hotho and Gerd Stumme.
[BibTeX]
Proceedings of the LWA 2010 - Lernen, Wissen, Adaptivität.
Technical report (KIS), 2010-10.
Department of Electrical Engineering/Computer Science, Kassel University, 2010.
Martin Atzmueller, Dominik Benz, Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Academic Publication Management with PUMA - collect, organize and share publications.
In: M. Lalmas, J. Jose, A. Rauber, F. Sebastiani and I. Frommholz, editors,
Proceedings of the European Conference on Research and Advanced Technology for Digital Libraries (ECDL) 2010, volume 6273, series Lecture Notes in Computer Science, pages 417-420.
Springer, Berlin/Heidelberg, 2010.
Dominik Benz, Andreas Hotho, Robert Jäschke, Gerd Stumme, Axel Halle, Angela Gerlach Sanches Lima, Helge Steenweg and Sven Stefani.
[doi]
[abstract]
[BibTeX]
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.
Query Logs as Folksonomies.
Datenbank-Spektrum, 10(1):15-24, 2010.
Dominik Benz, Andreas Hotho, Robert Jäschke, Beate Krause and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
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.
Dominik Benz, Andreas Hotho, Stefan Stützer and Gerd Stumme.
[doi]
[BibTeX]
The social bookmark and publication management system bibsonomy.
The VLDB Journal, 19:849-875, 2010.
Dominik Benz, Andreas Hotho, Robert Jäschke, Beate Krause, Folke Mitzlaff, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Social Bookmarking Systems: Verbosity Improves Semantics.
In:
Proceedings of INSNA Sunbelt XXX.
Riva del Garda Fierecongressi, Trento, Italy, 2010.
Christian Körner, Dominik Benz, Andreas Hotho, Markus Strohmaier and Gerd Stumme.
[BibTeX]
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.
Christian Körner, Dominik Benz, Markus Strohmaier, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Community Assessment using Evidence Networks.
In:
Proceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010).
Barcelona, Spain, 2010.
Folke Mitzlaff, Martin Atzmüller, Dominik Benz, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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 socialbookmarking application BibSonomy. The results indicate that the evidencenetworks reflect the relative rating of the explicit ones very well.
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.
Toronto, Canada, 2010.
(to appear)
Folke Mitzlaff, Dominik Benz, Gerd Stumme and Andreas Hotho.
[doi]
[BibTeX]
Characterizing Semantic Relatedness of Search Query Terms.
In:
Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009).
Bled, Slovenia, 2009.
Dominik Benz, Beate Krause, G. Praveen Kumar, Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Managing publications and bookmarks with BibSonomy.
In: C. Cattuto, G. Ruffo and F. Menczer, editors,
HT '09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia, pages 323-324.
ACM, New York, NY, USA, 2009.
Dominik Benz, Folke Eisterlehner, Andreas Hotho, Robert Jäschke, Beate Krause and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
In this demo we present BibSonomy, a social bookmark and publication sharing system.
Social Bookmarking am Beispiel BibSonomy.
In:
A. Blumauer and T. Pellegrini, editors,
Social Semantic Web, chapter 18, pages 363-391.
Springer, Berlin, Heidelberg, 2009.
Andreas Hotho, Robert Jäschke, Dominik Benz, Miranda Grahl, Beate Krause, Christoph Schmitz and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitungder 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.
Evaluating Similarity Measures for Emergent Semantics of Social Tagging.
In:
18th International World Wide Web Conference, pages 641-641.
2009.
Benjamin Markines, Ciro Cattuto, Filippo Menczer, Dominik Benz, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
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), series Studies in Classification, Data Analysis, and Knowledge Organization.
Springer, Berlin-Heidelberg, 2008.
in press
Korinna Bade and Dominik Benz.
[doi]
[abstract]
[BibTeX]
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.
Analyzing Tag Semantics Across Collaborative Tagging Systems.
In: H. Alani, S. Staab and G. Stumme, editors,
Proceedings of the Dagstuhl Seminar on Social Web Communities.
2008.
Dominik Benz, Marko Grobelnik, Andreas Hotho, Robert Jäschke, Dunja Mladenic, Vito D. P. Servedio, Sergej Sizov and Martin Szomszor.
[doi]
[abstract]
[BibTeX]
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.
Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems.
In:
Proceedings of the 3rd Workshop on Ontology Learning and Population (OLP3), pages 39-43.
Patras, Greece, 2008.
ISBN 978-960-89282-6-8
Ciro Cattuto, Dominik Benz, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Semantic Grounding of Tag Relatedness in Social Bookmarking Systems.
In: A. P. Sheth, S. Staab, M. Dean, M. Paolucci, D. Maynard, T. W. Finin and K. Thirunarayan, editors,
The Semantic Web - ISWC 2008, Proc.Intl. Semantic Web Conference 2008, volume 5318, series LNAI, pages 615-631.
Springer, Heidelberg, 2008.
Ciro Cattuto, Dominik Benz, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
ECML PKDD Discovery Challenge 2008 (RSDC'08).
2008.
[doi]
[BibTeX]
Position Paper: Ontology Learning from Folksonomies.
In: A. Hinneburg, editor,
Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007), pages 109-112.
Martin-Luther-Universität Halle-Wittenberg, 2007.
http://lwa07.informatik.uni-halle.de/kdml07/kdml07.htm
Dominik Benz and Andreas Hotho.
[doi]
[abstract]
[BibTeX]
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.
Supporting Collaborative Hierarchical Classification: Bookmarks as an Example.
Special Issue of the Computer Networks journal on Innovations in Web Communications Infrastructure, 51(16):4574-4585, 2007.
Dominik Benz, Karen H. L. Tso and Lars Schmidt-Thieme.
[doi]
[abstract]
[BibTeX]
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.
Interactive Thesaurus Assessment for Automatic Document Annotation.
In:
Proceedings of The Fourth International Conference on Knowledge Capture (K-CAP 2007), Whistler, Canada.
2007.
Kai Eckert, Heiner Stuckenschmidt and Magnus Pfeffer.
[pdf]
[BibTeX]
Automatic Bookmark Classification - A Collaborative Approach.
In:
Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006.
Edinburgh, Scotland, 2006.
isbn = 085432853X
Dominik Benz, Karen H. L. Tso and Lars Schmidt-Thieme.
[doi]
[abstract]
[BibTeX]
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.