Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.: Discovering Shared Conceptualizations in Folksonomies. In: Web Semantics: Science, Services and Agents on the World Wide Web 6 (2008), Nr. 1, S. 38-53
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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.

Jäschke, R.; Hotho, A.; Schmitz, C. & Stumme, G.: Analysis of the Publication Sharing Behaviour in BibSonomy. In: Priss, U.; Polovina, S. & Hill, R. (Hrsg.): Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007). Berlin, Heidelberg: Springer-Verlag, 2007 (Lecture Notes in Artificial Intelligence 4604), S. 283-295

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.

Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.: TRIAS - An Algorithm for Mining Iceberg Tri-Lattices. ICDM '06: Proceedings of the Sixth International Conference on Data Mining. Washington, DC, USA: IEEE Computer Society, 2006, S. 907-911
[Volltext]
In this paper, we present the foundations for mining frequent tri-concepts, which extend the notion of closed itemsets to three-dimensional data to allow for mining folk-sonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution as well as experimental results on a large real-world example.

Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.: TRIAS - An Algorithm for Mining Iceberg Tri-Lattices. Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06). Hong Kong: IEEE Computer Society, 2006, S. 907-911
[Volltext]