Illig, J.; Hotho, A.; Jäschke, R. & Stumme, G. (2011), A Comparison of content-based Tag Recommendations in Folksonomy Systems, in 'Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007)' , Springer, .
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Benz, D.; Hotho, A.; Jäschke, R.; Krause, B. & Stumme, G. (2010), 'Query Logs as Folksonomies', Datenbank-Spektrum 10 (1) , 15--24 .
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Query logs provide a valuable resource for preference information in search. A user clicking on a specific resource after submitting a query indicates that the resource has some relevance with respect to the query. To leverage the information ofquery logs, one can relate submitted queries from specific users to their clicked resources and build a tripartite graph ofusers, resources and queries. This graph resembles the folksonomy structure of social bookmarking systems, where users addtags to resources. In this article, we summarize our work on building folksonomies from query log files. The focus is on threecomparative studies of the system’s content, structure and semantics. Our results show that query logs incorporate typicalfolksonomy properties and that approaches to leverage the inherent semantics of folksonomies can be applied to query logsas well.

2008

Jäschke, R.; Krause, B.; Hotho, A. & Stumme, G. (2008), Logsonomy -- A Search Engine Folksonomy, in 'Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)' , AAAI Press, .
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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.

Krause, B.; Jäschke, R.; Hotho, A. & Stumme, G. (2008), Logsonomy - Social Information Retrieval with Logdata, in 'HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia' , ACM, New York, NY, USA , pp. 157--166 .
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Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today’s search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user’s information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.

Krause, B.; Schmitz, C.; Hotho, A. & Stumme, G. (2008), The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems, in 'Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web' .
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2007

Cattuto, C.; Schmitz, C.; Baldassarri, A.; Servedio, V. D. P.; Loreto, V.; Hotho, A.; Grahl, M. & Stumme, G. (2007), 'Network Properties of Folksonomies', AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering'' 20 (4) , 245-262 .
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Grahl, M.; Hotho, A. & Stumme, G. (2007), Conceptual Clustering of Social Bookmark Sites, in Alexander Hinneburg, ed., 'Workshop Proceedings of Lernen -- Wissensentdeckung -- Adaptivität (LWA 2007)' , Martin-Luther-Universität Halle-Wittenberg, , pp. 50-54 .
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Grahl, M.; Hotho, A. & Stumme, G. (2007), Conceptual Clustering of Social Bookmarking Sites, in '7th International Conference on Knowledge Management (I-KNOW '07)' , Know-Center, Graz, Austria , pp. 356-364 .
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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.

Jaeschke, R.; Marinho, L.; Hotho, A.; Schmidt-Thieme, L. & Stumme, G. (2007), Tag Recommendations in Folksonomies, in Alexander Hinneburg, ed., 'Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)' , Martin-Luther-Universität Halle-Wittenberg, , pp. 13-20 .
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Jäschke, R.; Hotho, A.; Schmitz, C. & Stumme, G. (2007), Analysis of the Publication Sharing Behaviour in BibSonomy, in U. Priss; S. Polovina & R. Hill, ed., 'Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007)' , Springer-Verlag, Berlin, Heidelberg , pp. 283--295 .
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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.

Schmitz, C.; Grahl, M.; Hotho, A.; Stumme, G.; Catutto, C.; Baldassarri, A.; Loreto, V. & Servedio, V. D. P. (2007), Network Properties of Folksonomies, in 'Proc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization''' .
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2006

Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G. (2006), Emergent Semantics in BibSonomy, in Christian Hochberger & Rüdiger Liskowsky, ed., 'Informatik 2006 -- Informatik für Menschen. Band 2' , Gesellschaft für Informatik, Bonn .
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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.

Hotho, A.; J?schke, R.; Schmitz, C. & Stumme, G. (2006), Information Retrieval in Folksonomies: Search and Ranking, in York Sure & John Domingue, ed., 'The Semantic Web: Research and Applications' , Springer, Heidelberg , pp. 411-426 .
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Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G. (2006), Information Retrieval in Folksonomies: Search and Ranking, in York Sure & John Domingue, ed., 'The Semantic Web: Research and Applications' , Springer, Heidelberg , pp. 411-426 .
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Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G. (2006), Trend Detection in Folksonomies, in Yannis S. Avrithis; Yiannis Kompatsiaris; Steffen Staab & Noel E. O'Connor, ed., 'Proc. First International Conference on Semantics And Digital Media Technology (SAMT) ' , Springer, Heidelberg , pp. 56-70 .
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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.

Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G. (2006), TRIAS - An Algorithm for Mining Iceberg Tri-Lattices, in 'Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06)' , IEEE Computer Society, Hong Kong , pp. 907-911 .
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Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G. (2006), Mining Association Rules in Folksonomies, in V. Batagelj; H.-H. Bock; A. Ferligoj & A. vZiberna, ed., 'Data Science and Classification: Proc. of the 10th IFCS Conf.' , Springer, Berlin, Heidelberg , pp. 261--270 .
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