Publikationen

Atzmueller, M.; Benz, D.; Hotho, A. & Stumme, G. (2011): Towards Mining Semantic Maturity in Social Bookmarking Systems. In: Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011), [Volltext]

Bloehdorn, S.; Blohm, S.; Cimiano, P.; Giesbrecht, E.; Hotho, A.; Lösch, U.; Mädche, A.; Mönch, E.; Sorg, P.; Staab, S. & Völker, J. (2011): Combining Data-Driven and Semantic Approaches for Text Mining.. In: Foundations for the Web of Information and Services, [Volltext]

2010

Berendt, B.; Hotho, A. & Stumme, G. (2010): Bridging the Gap-Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0. In: Web Semantics: Science, Services and Agents on the World Wide Web, Ausgabe/Number: 2-3, Vol. 8, Erscheinungsjahr/Year: 2010. Seiten/Pages: 95 - 96. [Volltext]

2009

Atzmueller, M.; Puppe, F. & Buscher, H.-P. (2009): A Semi-Automatic Approach for Confounding-Aware Subgroup Discovery. In: International Journal on Artificial Intelligence Tools (IJAIT), Ausgabe/Number: 1, Vol. 18, Erscheinungsjahr/Year: 2009. Seiten/Pages: 1 - 18.

Atzmueller, M. & Nalepa, G. J. (2009): A Textual Subgroup Mining Approach for Rapid ARD+ Model Capture. In: Proc. 22nd International Florida Artificial Intelligence Research Society Conference (FLAIRS), accepted,

Atzmueller, M. & Nalepa, G. J. (2009): Towards Rapid Knowledge Capture using Textual Subgroup Mining for Rule Prototyping. In: Technical Report 458, Institute of Computer Science, University of Würzburg, Erscheinungsjahr/Year: 2009.

2008

Atzmueller, M. & Seipel, D. (2008): Causal Subgroup Analysis for Detecting Confounding (Extended version). In: Proc. 18th International Conference on Applications of Declarative Programming and Knowledge Management, accepted,

Atzmueller, M. & Seipel, D. (2008): Declarative Specification of Ontological Domain Knowledge for Descriptive Data Mining (Extended version). In: Proc. 18th International Conference on Applications of Declarative Programming and Knowledge Management, accepted,

Atzmueller, M.; Beer, S.; Hörnlein, A.; Melcher, R.; Lührs, H. & Puppe, F. (2008): Design and Implementation of a Data Warehouse for Quality Management, System Evaluation and Knowledge Discovery in the Medical Domain. In: Proc. 1st European Workshop on Design, Evaluation and Refinement of Intelligent Systems, Erfurt.

(2008): Proceedings of the LWA 2008 - Lernen, Wissen, Adaptivität. Erscheinungsjahr/Year: 2008. Verlag/Publisher: Institute of Computer Science, University of Würzburg,

2006

(2006): Semantics, Web and Mining. Erscheinungsjahr/Year: 2006. Verlag/Publisher: Springer, Heidelberg. [Volltext]

Atzmueller, M. & Puppe, F. (2006): A Methodological View on Knowledge-Intensive Subgroup Discovery. In: Proc. 15th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2006),

2005

Berendt, B.; Hotho, A. & Stumme, G. (2005): Semantic Web Mining and the Representation, Analysis, and Evolution of Web Space. In: Proc. of the 1st Intl. Workshop on Representation and Analysis of Web Space, [Volltext]

2004

Berendt, B.; Hotho, A.; Mladenic, D.; van Someren, M.; Spiliopoulou, M. & Stumme, G. (2004): A Roadmap for Web Mining: From Web to Semantic Web.. In: Web Mining: From Web to Semantic Web, Heidelberg. [Volltext]

@inproceedings{berendt2004roadmap,
  author = {Berendt, Bettina and Hotho, Andreas and Mladenic, Dunja and van Someren, Maarten and Spiliopoulou, Myra and Stumme, Gerd},
  title = {A Roadmap for Web Mining: From Web to Semantic Web.},
  editor = {Berendt, Bettina and Hotho, Andreas and Mladenic, Dunja and van Someren, Maarten and Spiliopoulou, Myra and Stumme, Gerd},
  booktitle = {Web Mining: From Web to Semantic Web},
  publisher = {Springer},
  address = {Heidelberg},
  year = {2004},
  volume = {3209},
  pages = {1-22},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt2004roadmap.pdf},
  keywords = {2004, ecml, ewmf, itegpub, l3s, mining, myown, pkdd, proceedings, roadmap, semantic, web, workshop},
  abstract = {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.}
  }

Berendt, B.; Hotho, A. & Stumme, G. (2004): Usage Mining for and on the Semantic Web. In: Data Mining Next Generation Challenges and Future Directions. Hrsg./Editors: Kargupta, H.; Joshi, A.; Sivakumar, K. & Yesha, Y. Verlag/Publisher: AAAI Press, Boston. Erscheinungsjahr/Year: 2004. Seiten/Pages: 461-481. [Volltext]

(2004): Web Mining: From Web to Semantic Web, First European Web
Mining Forum, EMWF 2003, Cavtat-Dubrovnik, Croatia, September
22, 2003, Revised Selected and Invited Papers. LNAI Heidelberg
[Volltext]

2003

Atzmueller, M.; Baumeister, J. & Puppe, F. (2003): Evaluation of two Strategies for Case-Based Diagnosis handling Multiple Faults. In: Proc. 2nd Conf. Professional Knowledge Management (WM2003), Luzern, Switzerland.