Andreas Schmidt

Hinweis: Andreas Schmidt ist seit dem 31.10.2019 nicht mehr im Fachgebiet beschäftigt.
Email: schmidt@cs.uni-kassel.de

Projects

fee

Teaching

Supervised Theses

  • Florian Fassing: Exceptional Model Mining zur Entdeckung Abnormaler Communities
  • Linus Bunk: Extraktion und Analyse bipartiter Graphen in DBpedia

Winter Semester 2018/2019

Summer Semester 2018

Winter Semester 2017/2018

Summer Semester 2017

Winter Semester 2016/2017

Summer Semester 2016

Winter Semester 2015/2016

Summer Semester 2015

Publications

2018

  • 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).

2017

  • 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).
  • 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).
  • 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).
  • 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).

2016

  • 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).
  • 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).
  • 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).
  • 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).
  • 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).
  • 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).

2015

  • 1.
    Schmidt, A., Atzmueller, M., Stumme, G.: The FEE Project: Introduction and First Insights. In: Proc. UIS Workshop (2015).

Selected Activities

  • PC Member:  18th International Semantic Web Conference (ISWC 2019),  October 26 – 30, 2019, Auckland, New Zealand
  • Subreviewer: 2019 European Conference on Machine Learning and Principles and PKDD (ECMLPKDD 2019), September 16 – 20, 2019, Würzburg, Germany
  • Subreviewer: 11th ACM Conference on Web Science(WebSci’19), June 30 – July 3, 2019, Boston, MA, USA​
  • Subreviewer: 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD’19), August 4 – 8, 2019, Anchorage, Alaska, USA
  • Subreviewer: 2018 European Conference on Machine Learning and Principles and PKDD (ECMLPKDD 2018), September 10 – 14, 2018, Dublin, Ireland
  • Subreviewer: 27th International World Wide Web Conference (WWW 2018), April 23 – 27, 2018, Lyon, France
  • Subreviewer: 2017 European Conference on Machine Learning and Principles and PKDD (ECMLPKDD) 2017, September 18 – 22, 2017, Skopje, Macedonia
  • Subreviewer: 15th International Semantic Web Conference (ISWC 2016), October 16 – 21, 2016, Kobe, Japan
  • Subreviewer: 22nd Annual ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD 2016), August 13 – 17, 2016, San Francisco, California
  • Subreviewer: 13th Extended Semantic Web Conference (ESWC 2016), May 29 – June 17, 2016, Heraklion, Crete, Greece
  • Subreviewer: 25th International World Wide Web Conference (WWW 2016), April 11 – 15, 2016, Montreal, Canada
  • Subreviewer: 2016 IEEE International Conference on Data Mining (ICDM 2016), December 12 – 15, 2016, Barcelona, Spain
  • Subreviewer: 2016 IEEE International Conference on Data Mining (ICDM 2016), December 12 – 15, 2016, Barcelona, Spain
  • Subreviewer: 21st Annual ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), August 10 – 13, 2015, Sydney, Australia
  • Subreviewer: 14th International Semantic Web Conference (ISWC 2015), October 11 – 15, 2015, Bethlehem, PA, USA
  • Subreviewer: 2015 IEEE International Conference on Data Mining (ICDM 2015), November 14 – 17, Atlantic City, NJ, USA