Discovering Shared Conceptualizations in Folksonomies
Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.
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.
Analysis of the Publication Sharing Behaviour in BibSonomy
Jäschke, R.; Hotho, A.; Schmitz, C. & Stumme, G.
Priss, U.; Polovina, S. & Hill, R., ed., 'Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007)', 4604(), Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, Heidelberg, 283-295 (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.
BibSonomy: A Social Bookmark and Publication Sharing System
Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.
Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies and briefly describe our own system BibSonomy, which allows for sharing both bookmarksand publication references in a kind of personal library.
Emergent Semantics in BibSonomy
Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.
Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies, briefly describeour own system BibSonomy, which allows for sharing both bookmarks andpublication references, and discuss first steps towards emergent semantics.
Trend Detection in Folksonomies
Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.
As the number of resources on the web exceeds by far the number ofdocuments one can track, it becomes increasingly difficult to remainup to date on ones own areas of interest. The problem becomes moresevere with the increasing fraction of multimedia data, from whichit is difficult to extract some conceptual description of theircontents.One way to overcome this problem are social bookmark tools, whichare rapidly emerging on the web. In such systems, users are settingup lightweight conceptual structures called folksonomies, andovercome thus the knowledge acquisition bottleneck. As more and morepeople participate in the effort, the use of a common vocabularybecomes more and more stable. We present an approach for discoveringtopic-specific trends within folksonomies. It is based on adifferential adaptation of the PageRank algorithm to the triadichypergraph structure of a folksonomy. The approach allows for anykind of data, as it does not rely on the internal structure of thedocuments. In particular, this allows to consider different datatypes in the same analysis step. We run experiments on a large-scalereal-world snapshot of a social bookmarking system.
TRIAS - An Algorithm for Mining Iceberg Tri-Lattices
Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.
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 folksonomies. 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.