Discovering Shared Conceptualizations in Folksonomies.
Journal of Web Semantics, 6(1):38-53, 2008.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[BibTeX]
Logsonomy - A Search Engine Folksonomy.
In:
Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008).
AAAI Press, 2008.
Robert Jäschke, Beate Krause, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
In social bookmarking systems users describe bookmarksby keywords called tags. The structure behindthese social systems, called folksonomies, can beviewed as a tripartite hypergraph of user, tag and resourcenodes. This underlying network shows specificstructural properties that explain its growth and the possibilityof serendipitous exploration.Search engines filter the vast information of the web.Queries describe a user’s information need. In responseto the displayed results of the search engine, users clickon the links of the result page as they expect the answerto be of relevance. The clickdata can be represented as afolksonomy in which queries are descriptions of clickedURLs. This poster analyzes the topological characteristicsof the resulting tripartite hypergraph of queries,users and bookmarks of two query logs and compares ittwo a snapshot of the folksonomy del.icio.us.
The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems.
In:
Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web.
2008.
Beate Krause, Christoph Schmitz, Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Network Properties of Folksonomies.
AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering'', 20(4):245-262, 2007.
Ciro Cattuto, Christoph Schmitz, Andrea Baldassarri, Vito D. P. Servedio, Vittorio Loreto, Andreas Hotho, Miranda Grahl and Gerd Stumme.
[doi]
[BibTeX]
Conceptual Clustering of Social Bookmark Sites.
In: A. Hinneburg, editor,
Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007), pages 50-54.
Martin-Luther-Universität Halle-Wittenberg, 2007.
Miranda Grahl, Andreas Hotho and Gerd Stumme.
[doi]
[BibTeX]
Conceptual Clustering of Social Bookmarking Sites.
In:
7th International Conference on Knowledge Management (I-KNOW '07), pages 356-364.
Know-Center, Graz, Austria, 2007.
Miranda Grahl, Andreas Hotho and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of thesystem, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio.us bookmarking system.
Tag Recommendations in Folksonomies.
In: J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic and A. Skowron, editors,
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, volume 4702, series Lecture Notes in Computer Science, pages 506-514.
Springer, Berlin, Heidelberg, 2007.
Robert Jäschke, Leandro Balby Marinho, Andreas Hotho, Lars Schmidt-Thieme and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
Collaborative tagging systems allow users to assign keywords—so called “tags”—to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.
In this paper we evaluate and compare two recommendation algorithms on largescale real life datasets: an adaptation of user-based collaborative filtering and a graph-based recommender built on top of FolkRank. We show that both provide better results than non-personalized baseline methods. Especially the graph-based recommender outperforms existing methods considerably.
TRIAS - An Algorithm for Mining Iceberg Tri-Lattices.
In:
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06), pages 907-911.
IEEE Computer Society, Hong Kong, 2006.
Robert Jäschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter and Gerd Stumme.
[doi]
[BibTeX]