@inproceedings{mitzlaff2011community, author = {Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd}, title = {Community Assessment using Evidence Networks}, booktitle = {Analysis of Social Media and Ubiquitous Data}, series = {LNAI}, year = {2011}, volume = {6904}, keywords = {2011, community, itegpub, knowledge, mining, myown} }

%0 = inproceedings %A = Mitzlaff, Folke and Atzmueller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd %B = Analysis of Social Media and Ubiquitous Data %D = 2011 %T = Community Assessment using Evidence Networks

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.

@article{benz2010query, author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd}, title = {Query Logs as Folksonomies}, journal = {Datenbank-Spektrum}, year = {2010}, volume = {10}, number = {1}, pages = {15--24}, url = {http://dx.doi.org/10.1007/s13222-010-0004-8}, keywords = {2010, folksonomy, itegpub, logsonomy, myown}, 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. } }

%0 = article %A = Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd %D = 2010 %T = Query Logs as Folksonomies %U = http://dx.doi.org/10.1007/s13222-010-0004-8

@inproceedings{benz2010semantics, author = {Benz, Dominik and Hotho, Andreas and Stützer, Stefan and Stumme, Gerd}, title = {Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge}, booktitle = {Proceedings of the 2nd Web Science Conference (WebSci10)}, address = {Raleigh, NC, USA}, year = {2010}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2010semantics.pdf}, keywords = {2010, ibm-kde-tagging, itegpub, myown, ol_web2.0, semantics, web_science, websci, websci10} }

%0 = inproceedings %A = Benz, Dominik and Hotho, Andreas and Stützer, Stefan and Stumme, Gerd %B = Proceedings of the 2nd Web Science Conference (WebSci10) %C = Raleigh, NC, USA %D = 2010 %T = Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge %U = http://www.kde.cs.uni-kassel.de/pub/pdf/benz2010semantics.pdf

Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise�?, and (iii) in learning ontologies.

@inproceedings{koerner2010stop, author = {Körner, Christian and Benz, Dominik and Strohmaier, Markus and Hotho, Andreas and Stumme, Gerd}, title = {Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity}, booktitle = {Proceedings of the 19th International World Wide Web Conference (WWW 2010)}, publisher = {ACM}, address = {Raleigh, NC, USA}, year = {2010}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/koerner2010stop.pdf}, keywords = {2010, collaborative_verbosity, emergentsemantics_factors, ibm-kde-tagging, itegpub, myown, ol_web2.0, www, www2010}, abstract = {Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise�?, and (iii) in learning ontologies.} }

%0 = inproceedings %A = Körner, Christian and Benz, Dominik and Strohmaier, Markus and Hotho, Andreas and Stumme, Gerd %B = Proceedings of the 19th International World Wide Web Conference (WWW 2010) %C = Raleigh, NC, USA %D = 2010 %I = ACM %T = Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity %U = http://www.kde.cs.uni-kassel.de/pub/pdf/koerner2010stop.pdf

@inproceedings{benz2009characterizing, author = {Benz, Dominik and Krause, Beate and Kumar, G. Praveen and Hotho, Andreas and Stumme, Gerd}, title = {Characterizing Semantic Relatedness of Search Query Terms}, booktitle = {Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009)}, address = {Bled, Slovenia}, year = {2009}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2009characterizing.pdf}, keywords = {2009, ecml_pkdd, ein, itegpub, logsonomies, myown, similarity_measures, workshop, ol_web2.0, widely_related} }

%0 = inproceedings %A = Benz, Dominik and Krause, Beate and Kumar, G. Praveen and Hotho, Andreas and Stumme, Gerd %B = Proceedings of the 1st Workshop on Explorative Analytics of Information Networks (EIN2009) %C = Bled, Slovenia %D = 2009 %T = Characterizing Semantic Relatedness of Search Query Terms %U = http://www.kde.cs.uni-kassel.de/pub/pdf/benz2009characterizing.pdf

In this demo we present BibSonomy, a social bookmark and publication sharing system.

@inproceedings{benz2009managing, author = {Benz, Dominik and Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd}, title = {Managing publications and bookmarks with BibSonomy}, editor = {Cattuto, Ciro and Ruffo, Giancarlo and Menczer, Filippo}, booktitle = {HT '09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia}, publisher = {ACM}, address = {New York, NY, USA}, year = {2009}, pages = {323--324}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2009managing.pdf}, doi = {10.1145/1557914.1557969}, isbn = {978-1-60558-486-7}, keywords = {web20, ht09, 2009, social-bookmarking, social-software, bibsonomy, myown, itegpub}, abstract = {In this demo we present BibSonomy, a social bookmark and publication sharing system.} }

%0 = inproceedings %A = Benz, Dominik and Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd %B = HT '09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia %C = New York, NY, USA %D = 2009 %I = ACM %T = Managing publications and bookmarks with BibSonomy %U = http://www.kde.cs.uni-kassel.de/pub/pdf/benz2009managing.pdf

@book{alani2008proceedings,, title = {Proceedings of the Dagstuhl Seminar on Social Web Communities}, editor = {Alani, Harith and Staab, Steffen and Stumme, Gerd}, publisher = {Schloss Dagstuhl}, year = {2008}, url = {http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=08391}, keywords = {2008, communities, dagstuhl, social, web, tagorapub, tagora, itegpub} }

%0 = book %D = 2008 %I = Schloss Dagstuhl %T = Proceedings of the Dagstuhl Seminar on Social Web Communities %U = http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=08391

Several learning tasks comprise hierarchies. Comparison with a "goldstandard" is often performed to evaluate the quality of a learned hierarchy. We assembled various similarity metrics that have been proposed in different disciplines and compared them in a unified interdisciplinary framework for hierarchical evaluation which is based on the distinction of three fundamental dimensions. Identifying deficiencies for measuring structural similarity, we suggest three new measures for this purpose, either extending existing ones or based on new ideas. Experiments with an artificial dataset were performed to compare the different measures. As shown by our results, the measures vary greatly in their properties.

@inproceedings{bade2008evaluation, author = {Bade, Korinna and Benz, Dominik}, title = {Evaluation Strategies for Learning Algorithms of Hierarchical Structures}, booktitle = {Proceedings of the 32nd Annual Conference of the German Classification Society - Advances in Data Analysis, Data Handling and Business Intelligence (GfKl 2008)}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, publisher = {Springer}, address = {Berlin-Heidelberg}, year = {2008}, note = {in press}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/bade2008evaluation.pdf}, keywords = {2008, evaluation_strategies, hiearchies, itegpub, myown, ol_web2.0, widely_related}, abstract = {Several learning tasks comprise hierarchies. Comparison with a "goldstandard" is often performed to evaluate the quality of a learned hierarchy. We assembled various similarity metrics that have been proposed in different disciplines and compared them in a unified interdisciplinary framework for hierarchical evaluation which is based on the distinction of three fundamental dimensions. Identifying deficiencies for measuring structural similarity, we suggest three new measures for this purpose, either extending existing ones or based on new ideas. Experiments with an artificial dataset were performed to compare the different measures. As shown by our results, the measures vary greatly in their properties.} }

%0 = inproceedings %A = Bade, Korinna and Benz, Dominik %B = Proceedings of the 32nd Annual Conference of the German Classification Society - Advances in Data Analysis, Data Handling and Business Intelligence (GfKl 2008) %C = Berlin-Heidelberg %D = 2008 %I = Springer %T = Evaluation Strategies for Learning Algorithms of Hierarchical Structures %U = http://www.kde.cs.uni-kassel.de/pub/pdf/bade2008evaluation.pdf

The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.

@inproceedings{benz2008analyzing, author = {Benz, Dominik and Grobelnik, Marko and Hotho, Andreas and Jäschke, Robert and Mladenic, Dunja and Servedio, Vito D. P. and Sizov, Sergej and Szomszor, Martin}, title = {Analyzing Tag Semantics Across Collaborative Tagging Systems}, editor = {Alani, Harith and Staab, Steffen and Stumme, Gerd}, booktitle = {Proceedings of the Dagstuhl Seminar on Social Web Communities}, year = {2008}, number = {08391}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2008analyzing.pdf}, keywords = {2008, dagstuhl, iin2009, itegpub, myown, tag_semantics, tagorapub, ol_web2.0, widely_related}, abstract = {The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance.} }

%0 = inproceedings %A = Benz, Dominik and Grobelnik, Marko and Hotho, Andreas and Jäschke, Robert and Mladenic, Dunja and Servedio, Vito D. P. and Sizov, Sergej and Szomszor, Martin %B = Proceedings of the Dagstuhl Seminar on Social Web Communities %D = 2008 %T = Analyzing Tag Semantics Across Collaborative Tagging Systems %U = http://www.kde.cs.uni-kassel.de/pub/pdf/benz2008analyzing.pdf

Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For taskslike synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.

@inproceedings{cattuto2008semantica, author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd}, title = {Semantic Grounding of Tag Relatedness in Social Bookmarking Systems}, editor = {Sheth, Amit P. and Staab, Steffen and Dean, Mike and Paolucci, Massimo and Maynard, Diana and Finin, Timothy W. and Thirunarayan, Krishnaprasad}, booktitle = {The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008}, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2008}, volume = {5318}, pages = {615--631}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2008semantica.pdf}, doi = {http://dx.doi.org/10.1007/978-3-540-88564-1_39}, keywords = {2008, grounding, iswc2008, itegpub, myown, relatedness, semantic, similarity, sw, tag, tagging, tagorapub, ol_web2.0, methods_concepts, methods_concepthierarchy, semantic_relatedness}, abstract = {Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For taskslike synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.} }

%0 = inproceedings %A = Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd %B = The Semantic Web -- ISWC 2008, Proc.Intl. Semantic Web Conference 2008 %C = Heidelberg %D = 2008 %I = Springer %T = Semantic Grounding of Tag Relatedness in Social Bookmarking Systems %U = http://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2008semantica.pdf

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.

@inproceedings{jaeschke2008logsonomy, author = {Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd}, title = {Logsonomy -- A Search Engine Folksonomy}, booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)}, publisher = {AAAI Press}, year = {2008}, url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf}, keywords = {2008, search, engine, logsonomy, logsonomies, folksonomy, tagorapub, folksonomies, itegpub}, 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.} }

%0 = inproceedings %A = Jäschke, Robert and Krause, Beate and Hotho, Andreas and Stumme, Gerd %B = Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008) %D = 2008 %I = AAAI Press %T = Logsonomy -- A Search Engine Folksonomy %U = http://www.kde.cs.uni-kassel.de/hotho/pub/2008/Krause2008logsonomy_short.pdf

@inproceedings{krause2008comparison, author = {Krause, Beate and Hotho, Andreas and Stumme, Gerd}, title = {A Comparison of Social Bookmarking with Traditional Search}, editor = {Macdonald, Craig and Ounis, Iadh and Plachouras, Vassilis and Ruthven, Ian and White, Ryen W.}, booktitle = {30th European Conference on IR Research, ECIR 2008}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, address = {Glasgow, UK}, year = {2008}, volume = {4956}, pages = {101-113}, isbn = {978-3-540-78645-0}, keywords = {2008, nopaper, bookmarking, social, logsonomies, tagorapub, itegpub} }

%0 = inproceedings %A = Krause, Beate and Hotho, Andreas and Stumme, Gerd %B = 30th European Conference on IR Research, ECIR 2008 %C = Glasgow, UK %D = 2008 %I = Springer %T = A Comparison of Social Bookmarking with Traditional Search

@inproceedings{krause2008antisocialb, author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd}, title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems}, booktitle = {Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web}, year = {2008}, url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf}, keywords = {2008, systems, bookmarking, web, tagger, 2.0, itegpub, social, web2.0, folksonomy, folksonomies, tagorapub, spam} }

%0 = inproceedings %A = Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd %B = Proc. of the Fourth International Workshop on Adversarial Information Retrieval on the Web %D = 2008 %T = The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems %U = http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf

Bookmarks (or favorites, hotlists) are popular strategies to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbor-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. A prototype system called CariBo has been implemented as a plugin for the central bookmark server software SiteBar. All findings have been evaluated on a reasonably large scale, real user dataset with promising results, and possible implications for shared and social bookmarking systems are discussed.

@article{benz2007supporting, author = {Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars}, title = {Supporting Collaborative Hierarchical Classification: Bookmarks as an Example}, journal = {Special Issue of the Computer Networks journal on Innovations in Web Communications Infrastructure}, year = {2007}, volume = {51}, number = {16}, pages = {4574--4585}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2007supporting.pdf}, doi = {http://dx.doi.org/10.1016/j.comnet.2007.06.014}, keywords = {studienarbeit, 2007, myown, itegpub}, abstract = {Bookmarks (or favorites, hotlists) are popular strategies to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbor-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. A prototype system called CariBo has been implemented as a plugin for the central bookmark server software SiteBar. All findings have been evaluated on a reasonably large scale, real user dataset with promising results, and possible implications for shared and social bookmarking systems are discussed.} }

%0 = article %A = Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars %D = 2007 %T = Supporting Collaborative Hierarchical Classification: Bookmarks as an Example %U = http://www.kde.cs.uni-kassel.de/pub/pdf/benz2007supporting.pdf

@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}, title = {Network Properties of Folksonomies}, editor = {Hoche, Susanne and Nürnberger, Andreas and Flach, Jürgen}, journal = {AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''}, publisher = {IOS Press}, year = {2007}, volume = {20}, number = {4}, pages = {245-262}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf}, issn = {0921-7126}, keywords = {2007, semantics, emergent, folksonomy, tagorapub, folksonomies, l3s, network, itegpub, fca} }

%0 = article %A = 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 %D = 2007 %I = IOS Press %T = Network Properties of Folksonomies %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2007/cattuto2007network.pdf

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.

@inproceedings{grahl2007conceptuala, author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd}, title = {Conceptual Clustering of Social Bookmarking Sites}, booktitle = {7th International Conference on Knowledge Management (I-KNOW '07)}, publisher = {Know-Center}, address = {Graz, Austria}, year = {2007}, pages = {356-364}, url = {http://www.tagora-project.eu/wp-content/2007/06/grahl_iknow07.pdf}, keywords = {sites, 2007, tagging, social, folksonomy, tagorapub, folksonomies, itegpub}, 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.} }

%0 = inproceedings %A = Grahl, Miranda and Hotho, Andreas and Stumme, Gerd %B = 7th International Conference on Knowledge Management (I-KNOW '07) %C = Graz, Austria %D = 2007 %I = Know-Center %T = Conceptual Clustering of Social Bookmarking Sites %U = http://www.tagora-project.eu/wp-content/2007/06/grahl_iknow07.pdf

@inproceedings{jaeschke2007organizing, author = {Jäschke, Robert and Grahl, Miranda and Hotho, Andreas and Krause, Beate and Schmitz, Christoph and Stumme, Gerd}, title = {Organizing Publications and Bookmarks in BibSonomy}, editor = {Alani, Harith and Noy, Natasha and Stumme, Gerd and Mika, Peter and Sure, York and Vrandecic, Denny}, booktitle = {Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007}, address = {Banff, Canada}, year = {2007}, url = {http://www2007.org/workshops/paper_25.pdf}, keywords = {challenge, 2007, organizing, BibSonomy, bibsonomy, tagorapub, l3s, itegpub} }

%0 = inproceedings %A = Jäschke, Robert and Grahl, Miranda and Hotho, Andreas and Krause, Beate and Schmitz, Christoph and Stumme, Gerd %B = Workshop on Social and Collaborative Construction of Structured Knowledge (CKC 2007) at WWW 2007 %C = Banff, Canada %D = 2007 %T = Organizing Publications and Bookmarks in BibSonomy %U = http://www2007.org/workshops/paper_25.pdf

Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.

@inproceedings{benz2006automatic, author = {Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars}, title = {Automatic Bookmark Classification - A Collaborative Approach}, booktitle = {Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006}, address = {Edinburgh, Scotland}, year = {2006}, note = {isbn = 085432853X}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2006automatic.pdf}, keywords = {studienarbeit, www2006, 2006, myown, iwi, itegpub}, abstract = {Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.} }

%0 = inproceedings %A = Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars %B = Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006 %C = Edinburgh, Scotland %D = 2006 %T = Automatic Bookmark Classification - A Collaborative Approach %U = http://www.kde.cs.uni-kassel.de/pub/pdf/benz2006automatic.pdf

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.

@inproceedings{hotho2006emergent, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {Emergent Semantics in BibSonomy}, editor = {Hochberger, Christian and Liskowsky, Rüdiger}, booktitle = {Informatik 2006 -- Informatik für Menschen. Band 2}, series = {Lecture Notes in Informatics}, publisher = {Gesellschaft für Informatik}, address = {Bonn}, year = {2006}, volume = {P-94}, note = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf}, keywords = {2006, UniK, bibsonomy, emergence, emergent, folksonomy, hotho, itegpub, jaeschke, l3s, nepomuk, schmitz, semantics, stumme, tagorapub, ol_web2.0, emergentsemantics_evidence}, abstract = {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.} }

%0 = inproceedings %A = Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd %B = Informatik 2006 -- Informatik für Menschen. Band 2 %C = Bonn %D = 2006 %I = Gesellschaft für Informatik %T = Emergent Semantics in BibSonomy %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf

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.

@inproceedings{hotho2006trend, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {Trend Detection in Folksonomies}, editor = {Avrithis, Yannis S. and Kompatsiaris, Yiannis and Staab, Steffen and O'Connor, Noel E.}, booktitle = {Proc. First International Conference on Semantics And Digital Media Technology (SAMT) }, series = {LNCS}, publisher = {Springer}, address = {Heidelberg}, year = {2006}, volume = {4306}, pages = {56-70}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf}, isbn = {3-540-49335-2}, keywords = {intranet, 2006, trend, pagerank, hotho, schmitz, jaeschke, l3s, itegpub, detection, triadic, stumme, nepomuk, folksonomy, tagorapub, folkrank, UniK}, abstract = {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.} }

%0 = inproceedings %A = Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd %B = Proc. First International Conference on Semantics And Digital Media Technology (SAMT) %C = Heidelberg %D = 2006 %I = Springer %T = Trend Detection in Folksonomies %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf