@inproceedings{krause2008antisocialb, author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web}, interhash = {a45d40ac7776551301ad9dde5b25357f}, intrahash = {6357f535000a383f228f1e8e56ca86ca}, title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems}, url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf}, year = 2008 } @inproceedings{jaeschke2008logsonomy, abstract = {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.}, author = {Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, interhash = {13ec3f45fc7e0364cdc6b9a7c12c5c2c}, intrahash = {359e1eccdc524334d4a2ad51330f76ae}, publisher = {AAAI Press}, title = {Logsonomy -- A Search Engine Folksonomy}, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, year = 2008 } @article{jaeschke08discovering, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd}, interhash = {cfca594f9dbe30694bfbcdeb40dc4e88}, intrahash = {eb0bdaeab0aa5d4c528c97e2b10770b9}, journal = {Journal of Web Semantics}, number = 1, pages = {38-53}, title = {Discovering Shared Conceptualizations in Folksonomies}, url = {http://dx.doi.org/10.1016/j.websem.2007.11.004}, volume = 6, year = 2008 } @inproceedings{jaeschke2007tag, abstract = {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.}, address = {Berlin, Heidelberg}, author = {Jäschke, Robert and Marinho, Leandro Balby and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd}, booktitle = {Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases}, editor = {Kok, Joost N. and Koronacki, Jacek and de Mántaras, Ramon López and Matwin, Stan and Mladenic, Dunja and Skowron, Andrzej}, ee = {http://dx.doi.org/10.1007/978-3-540-74976-9_52}, interhash = {7e212e3bac146d406035adebff248371}, intrahash = {bb8ecec699a2f129322fe334747c6aef}, isbn = {978-3-540-74975-2}, pages = {506-514}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Tag Recommendations in Folksonomies}, url = {http://dx.doi.org/10.1007/978-3-540-74976-9_52}, volume = 4702, year = 2007 } @inproceedings{jaeschke06trias, address = {Hong Kong}, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd}, booktitle = {Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06)}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.162}, interhash = {b4964c3bdd2991a80873d7080ef6a73e}, intrahash = {e387c294129e11f4221514d5fa807e26}, isbn = {0-7695-2701-9}, issn = {1550-4786}, month = {December}, pages = {907-911}, publisher = {IEEE Computer Society}, title = {TRIAS - An Algorithm for Mining Iceberg Tri-Lattices}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/jaeschke2006trias.pdf}, vgwort = {19}, year = 2006 } @inproceedings{grahl07conceptualKdml, author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd}, booktitle = {Workshop Proceedings of Lernen -- Wissensentdeckung -- Adaptivität (LWA 2007)}, editor = {Hinneburg, Alexander}, interhash = {9c3bb05456bf11bcd88a1135de51f7d9}, intrahash = {6d5188d66564fe4ed7386e28868504de}, isbn = {978-3-86010-907-6}, month = sep, pages = {50-54}, publisher = {Martin-Luther-Universität Halle-Wittenberg}, title = {Conceptual Clustering of Social Bookmark Sites}, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2007/kdml_recommender_final.pdf}, vgwort = {14}, year = 2007 } @article{cattuto2007networkb, author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd}, editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen}, interhash = {fc5f2df61d28bc99b7e15029da125588}, intrahash = {da6c676c5664017247c7564fc247b190}, issn = {0921-7126}, journal = {AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''}, number = 4, pages = {245-262}, publisher = {IOS Press}, title = {Network Properties of Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf}, vgwort = {67}, volume = 20, year = 2007 } @inproceedings{grahl2007conceptuala, abstract = {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.}, address = {Graz, Austria}, author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd}, booktitle = {7th International Conference on Knowledge Management (I-KNOW '07)}, interhash = {5cf58d2fdd3c17f0b0c54ce098ff5b60}, intrahash = {334d3ab11400c4a3ea3ed5b1e95c1855}, issn = {0948-695x}, month = {September}, pages = {356-364}, publisher = {Know-Center}, title = {Conceptual Clustering of Social Bookmarking Sites}, url = {http://www.tagora-project.eu/wp-content/2007/06/grahl_iknow07.pdf}, year = 2007 } @inproceedings{jaeschke2008logsonomy, abstract = {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.}, author = {Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, interhash = {13ec3f45fc7e0364cdc6b9a7c12c5c2c}, intrahash = {359e1eccdc524334d4a2ad51330f76ae}, publisher = {AAAI Press}, title = {Logsonomy -- A Search Engine Folksonomy}, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, year = 2008 } @inproceedings{grahl2007conceptuala, abstract = {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.}, address = {Graz, Austria}, author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd}, booktitle = {7th International Conference on Knowledge Management (I-KNOW '07)}, interhash = {5cf58d2fdd3c17f0b0c54ce098ff5b60}, intrahash = {334d3ab11400c4a3ea3ed5b1e95c1855}, issn = {0948-695x}, month = {September}, pages = {356-364}, publisher = {Know-Center}, title = {Conceptual Clustering of Social Bookmarking Sites}, url = {http://www.tagora-project.eu/wp-content/2007/06/grahl_iknow07.pdf}, year = 2007 } @inproceedings{krause2008antisocialb, author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web}, interhash = {a45d40ac7776551301ad9dde5b25357f}, intrahash = {6357f535000a383f228f1e8e56ca86ca}, title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems}, url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf}, year = 2008 } @article{cattuto2007networkb, author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd}, editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen}, interhash = {fc5f2df61d28bc99b7e15029da125588}, intrahash = {da6c676c5664017247c7564fc247b190}, issn = {0921-7126}, journal = {AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''}, number = 4, pages = {245-262}, publisher = {IOS Press}, title = {Network Properties of Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf}, vgwort = {67}, volume = 20, year = 2007 } @inproceedings{hotho2006das, abstract = {Immer mehr Soziale-Lesezeichen-Systeme entstehen im heutigen Web. In solchen Systemen erstellen die Nutzer leichtgewichtige begriffliche Strukturen, so genannte Folksonomies. Ihren Erfolg verdanken sie der Tatsache, dass man keine speziellen Fähigkeiten benötigt, um an der Gestaltung mitzuwirken. In diesem Artikel beschreiben wir unser System BibSonomy. Es erlaubt das Speichern, Verwalten und Austauschen sowohl von Lesezeichen (Bookmarks) als auch von Literaturreferenzen in Form von BibTeX-Einträgen. Die Entwicklung des verwendeten Vokabulars und der damit einhergehenden Entstehung einer gemeinsamen Semantik wird detailliert diskutiert.}, address = {Baden-Baden}, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Social Software in der Wertschöpfung}, file = {hotho2006das.pdf:hotho2006das.pdf:PDF}, groups = {public}, interhash = {1b39e4a77cac919f9030601711aad543}, intrahash = {a333df6fdc7ff9322e3ce03988a7965e}, pdf = {E:\home\help_of_all_helps.pdf}, publisher = {Nomos}, timestamp = {2009-09-29 12:35:44}, title = {Das Entstehen von Semantik in BibSonomy}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006entstehen.pdf}, username = {dbenz}, year = 2006 } @article{benz2010query, abstract = {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. }, author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd}, interhash = {dae3931a5f445dc67bf111b26f753c36}, intrahash = {bf96c01262d15fb6eaaf558ecb9a9e69}, journal = {Datenbank-Spektrum}, month = jun, number = 1, pages = {15--24}, title = {Query Logs as Folksonomies}, url = {http://dx.doi.org/10.1007/s13222-010-0004-8}, volume = 10, year = 2010 } @incollection{springerlink:10.1007/978-3-642-14000-6_4, abstract = {Social resource sharing systems are central elements of the Web 2.0 and use all the same kind of lightweight knowledge representation, called folksonomy. As these systems are easy to use, they attract huge masses of users. Data Mining provides methods to analyze data and to learn models which can be used to support users. The application and adaptation of known data mining algorithms to folksonomies with the goal to support the users of such systems and to extract valuable information with a special focus on the Semantic Web is the main target of this paper. In this work we give a short introduction into folksonomies with a focus on our own system BibSonomy. Based on the analysis we made on a large folksonomy dataset, we present the application of data mining algorithms on three different tasks, namely spam detection, ranking and recommendation. To bridge the gap between folksonomies and the Semantic Web, we apply association rule mining to extract relations and present a deeper analysis of statistical measures which can be used to extract tag relations. This approach is complemented by presenting two approaches to extract conceptualizations from folksonomies.}, address = {Berlin / Heidelberg}, affiliation = {University of Kassel Knowledge & Data Engineering Group 34121 Kassel Germany}, author = {Hotho, Andreas}, booktitle = {Intelligent Information Access}, doi = {10.1007/978-3-642-14000-6_4}, editor = {Armano, Giuliano and de Gemmis, Marco and Semeraro, Giovanni and Vargiu, Eloisa}, interhash = {8995ce2ba8835668820622f8aae908fe}, intrahash = {1a7906f61b76a87f618e0db657f5c6d9}, pages = {57-82}, publisher = {Springer}, series = {Studies in Computational Intelligence}, title = {Data Mining on Folksonomies}, url = {http://dx.doi.org/10.1007/978-3-642-14000-6_4}, volume = 301, year = 2010 } @article{dominik2010query, abstract = {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.}, author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd}, interhash = {dae3931a5f445dc67bf111b26f753c36}, intrahash = {bf96c01262d15fb6eaaf558ecb9a9e69}, journal = {Datenbank-Spektrum}, month = {#jun#}, number = 1, pages = {15--24}, title = {Query Logs as Folksonomies}, url = {http://dx.doi.org/10.1007/s13222-010-0004-8}, volume = 10, year = 2010 } @inproceedings{schmitz2006mining, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.}, address = {Heidelberg}, author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd}, booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.}, editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and Žiberna, A.}, interhash = {20650d852ca3b82523fcd8b63e7c12d7}, intrahash = {11b2a59a568d246d7f36cb68169a464a}, month = {July}, pages = {261--270}, publisher = {Springer}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, title = {Mining Association Rules in Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf}, year = 2006 } @inproceedings{Jaeschke2008logsonomy, abstract = {In social bookmarking 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. Search engines filter the vast information of the web. Queries 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. The clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. This poster analyzes the topological characteristics of the resulting tripartite hypergraph of queries, users and bookmarks of two query logs and compares it two a snapshot of the folksonomy del.icio.us.}, author = {Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, interhash = {13ec3f45fc7e0364cdc6b9a7c12c5c2c}, intrahash = {359e1eccdc524334d4a2ad51330f76ae}, publisher = {AAAI Press}, title = {Logsonomy -- A Search Engine Folksonomy}, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, year = 2008 } @inproceedings{krause2008antisocial, author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web}, interhash = {a45d40ac7776551301ad9dde5b25357f}, intrahash = {6357f535000a383f228f1e8e56ca86ca}, title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems}, url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf}, year = 2008 } @inproceedings{grahl2007clustering, abstract = {Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the system, 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.}, address = {Graz, Austria}, author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd}, booktitle = {7th International Conference on Knowledge Management (I-KNOW '07)}, interhash = {5cf58d2fdd3c17f0b0c54ce098ff5b60}, intrahash = {334d3ab11400c4a3ea3ed5b1e95c1855}, issn = {0948-695x}, month = sep, pages = {356-364}, publisher = {Know-Center}, title = {Conceptual Clustering of Social Bookmarking Sites}, year = 2007 }