BibSonomy publications for /tag/tagoraThu Feb 17 17:42:29 CET 2011Baden-BadenSocial Software in der WertschöpfungDas Entstehen von Semantik in BibSonomy20062006 BibSonomy UniK association bibsonomy emergentsemantics_evidence folkrank folksonomies folksonomy hotho jaeschke nepomuk ol_web2.0 pagerank rules schmitz semantics semantik stumme tagging taggingsurvey tagora tagorapub tags 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.Tue Feb 08 15:56:07 CET 2011SeptemberProceedings of the Dagstuhl Seminar on Social Web Communities20082008 communities dagstuhl social web tagorapub tagora itegpub Mon Nov 08 13:33:25 CET 2010New York, NY, USAProceedings of the International Workshop on Modeling Social Media8:1--8:4MSM '10Friendship, collaboration and semantics in Flickr: from social interaction to semantic similarity20102010 flickr model myown network semantics similarity social statistics tagora Fri Dec 19 09:28:07 CET 2008SeptemberProceedings of the Dagstuhl Seminar on Social Web Communities20082008 communities dagstuhl itegpub myown social tagora tagorapub web Tue Sep 16 19:17:54 CEST 2008Mining Social Data (MSoDa) Workshop ProceedingsJuly26-30Analyzing Social Bookmarking Systems: A del.icio.us Cookbook2008delicious paper research statistics tagging tagora Social bookmarking systems have recently gained interest among researches in the areas of data mining and web intelligence, as they provide a vast amount of user-generated annotations and reflect the interests of millions of people. In this paper, we discuss our initial findings obtained from analyzing a vast corpus of almost 150 million bookmarks found at del.icio.us. Apart from investigating bookmarking and tagging patterns in this data, we discuss evidence that social bookmarking systems are vulnerable to spamming and hence need to be preprocessed before any insightful analysis can be carried out. We present a method, which limits the influence of spam in social bookmarking analysis and provide conclusions and directions for future research.Wed Jul 30 10:52:43 CEST 2008Proceedings of the WWW 2008 Poster SessionPersonalized Search and Exploration with MyTag20082008 MyTag braun dellschaft exploration franz hagen hering jungen koblenz metzler personalized rostilov saathoff search tagora tagorapub www Wed Jul 30 10:50:32 CEST 2008HYPERTEXT 2008, Proceedings of the 19th ACM Conference on Hypertext and HypermediaAn Epistemic Dynamic Model for Tagging Systems20082008 dellschaft dynamic epistemic hypertext koblenz model staab systems tagging tagora tagorapub In recent literature, several models were proposed for reproducing and understanding the tagging behavior of users. They all assume that the tagging behavior is influenced by the previous tag assignments of other users. But they are only partially successful in reproducing characteristic properties found in tag streams. We argue that this inadequacy of existing models results from their inability to include user’s background knowledge into their model of tagging behavior. This paper presents a generative tagging model that integrates both components, the background knowledge and the influence of previous tag assignments. Our model successfully reproduces characteristic properties of tag streams. It even explains effects of the user interface on the tag stream.Tue Jun 10 22:32:17 CEST 2008Baden-BadenSocial Software in der WertschöpfungDas Entstehen von Semantik in BibSonomy20062006 BibSonomy UniK association bibsonomy folkrank folksonomies folksonomy hotho jaeschke nepomuk pagerank rules schmitz semantics semantik stumme tagging tagora tagorapub tags 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.Tue Jun 10 14:05:05 CEST 2008Tag Recommendations in Folksonomies2007bibsonomy del.icio.us folkrank folksonomy kassel last.fm nepomuk paper read:2008 recommendation tagging tagora uni Sun Jun 08 12:59:40 CEST 20084th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0Folksonomies, the Semantic Web, and Movie Recommendation 2007collaborative filtering folksonomies imdb kind-of-tags movies netflix paper read:2008 recommendation semantic tagora tags web web2.0 While the Semantic Web has evolved to support the meaningful exchange of heterogeneous data through shared and controlled conceptualisations, Web 2.0 has demonstrated that large-scale community tagging sites can enrich the semantic web with readily accessible and valuable knowledge. In this paper, we investigate the integration of a movies folksonomy with a semantic knowledge base about user-movie rentals. The folksonomy is used to enrich the knowledge base with descriptions and categorisations of movie titles, and user interests and opinions. Using tags harvested from the Internet Movie Database, and movie rating data gathered by Netflix, we perform experiments to investigate the question that folksonomy-generated movie tag-clouds can be used to construct better user profiles that reflect a user’s level of interest in different kinds of movies, and therefore, provide a basis for prediction of their rating for a previously unseen movie.Fri Jun 06 11:48:57 CEST 2008ACM Confrence on Hypertext and HypermediaJuneCorrelating User Profiles from Multiple Folksonomies2008folksonomies tagora tagorapub user-profiles Fri Jun 06 11:48:35 CEST 20081st International Workshop on Collective Semantics: Collective Intelligence \& the Semantic Web (CISWeb 2008) JuneEnriching Ontological User Profiles with Tagging History for Multi-Domain Recommendations 2008recommendation-systems tag-filtering tagora tagorapub user-profiles Fri Jun 06 11:45:26 CEST 20084th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0Folksonomies, the Semantic Web, and Movie Recommendation 2007folksonomies imdb netflix recommendations tagora tagorapub Thu May 08 11:32:59 CEST 2008Proceedings of ECIR'08 Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 2008)3Introducing Triple Play for Improved Resource Retrieval in Collaborative Tagging Systems20082008 abbasi collaborative ecir esair folksonomies folksonomy information retrieval search staab system tagging tagora tagorapub tripleplay Collaborative tagging systems (like Flickr, del.icio.us, citeulike, etc.) are becoming more popular with passage of time. Users share their resources on tagging systems, and add keywords (called tags) to these resources. Users can search resources using these tags. But as the user gives more tags for search, he might not get sufficient search results, because the resources might not be tagged with all the related tags. We introduce the method Triple Play, which smoothes the tag space by user space for improved retrieval of resources. As a part of Triple Play, we also propose two new vector space models for collaborative tagging systems, SmoothVSM Dense and SmoothVSM Sparse. These vector space models exploit the user-tag co-occurrence relationship to overcome the problem of missing information in tagging systems. Finally we apply Latent Semantic Analysis to different vector space models and analyze the results. Initial experimentation show that using additional information available in tagging systems helps in improving search in tagging systems.Wed Mar 12 16:41:13 CET 2008OctStatistical physics of social dynamics2007loreto physics review social statistical tagora Statistical physics has proven to be a very fruitful framework to describe phenomena outside the realm of traditional physics. The last years have witnessed the attempt by physicists to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. Here we review the state of the art by focusing on three major research lines i.e., opinion, cultural and language dynamics. In addition we discuss other social phenomena, such as crowd behavior, hierarchy formation, human dynamics, social spreading. We highlight the connections between these problems and other, more traditional, topics of statistical physics. We also emphasize the comparison of model results with empirical data from social systems.Fri Feb 15 14:44:26 CET 2008Tampa Bay, USAProceedings of the Seventh International Workshop on Peer-to-Peer Systems, IPTPS08February{PINTS}: Peer-to-Peer Infrastructure for Tagging Systems2008görlitz p2p pints sizov staab tagging tagora tagorapub Sun Feb 10 02:19:38 CET 2008NovemberFolksonomy Definition and Wikipedia2005WW-MUST d41, folksonomy semantic tagging tagora text-mining wikipedia Fri Jan 04 16:59:10 CET 2008Graz, AustriaI-KNOW '07. 7th International Conference on Knowledge Management@PROCEEDINGS{ToMa07, title = {Proceedings of I-KNOW 2007}, year = {2007}, editor = {Tochtermann, Klaus and Maurer, Herrmann}, keywords = {knowledgemanagement iknow DISS ownstuff}, timestamp = {2007.11.06} }SeptemberConceptual Clustering of Social Bookmarking Sites20072007 DISS bookmarking clustering folkrank folksonomy iknow l3s myown ontologies semantics social tagging tagging_clustering tagging_efficiency tagging_semantics tagora tagorapub toread 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.Sat Oct 13 14:11:57 CEST 20074th International Workshop on Text-Based Information RetrievalAspects of Broad Folksonomies2007Tagora collaborative_tagging Folksonomies, collaboratively created sets of metadata, are becoming more and more important for organising in- formation and knowledge of communites in the Web. While for a single user the difference to keyword assignment is marginal, the power of folksonomies emerges from the col- laborative aspects. Folksonomies are already issue of re- search. Within this publication we analyse underlying sta- tistical properties of broad folksonomies aiming to iden- tify laws and characteristics, which allow inferring prop- erties for folksonomy based retrieval. The actual bene- fit of folksonomies for retrieval and the derived methods are concluded from experiments with aggregated data from del.icio.us.Mon Aug 06 11:39:48 CEST 20074th International Workshop on Text-Based Information RetrievalAspects of Broad Folksonomies2007broad ciro folksonomies paper retrieval tagora Folksonomies, collaboratively created sets of metadata, are becoming more and more important for organising in- formation and knowledge of communites in the Web. While for a single user the difference to keyword assignment is marginal, the power of folksonomies emerges from the col- laborative aspects. Folksonomies are already issue of re- search. Within this publication we analyse underlying sta- tistical properties of broad folksonomies aiming to iden- tify laws and characteristics, which allow inferring prop- erties for folksonomy based retrieval. The actual bene- fit of folksonomies for retrieval and the derived methods are concluded from experiments with aggregated data from del.icio.us.tagoraCommunity for tag(s) tagora