BibSonomy publications for /group/iteg/jaeschkeThu 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.Thu Feb 17 17:42:27 CET 2011BonnInformatik 2006 -- Informatik für Menschen. Band 2OctoberProc. Workshop on Applications of Semantic Technologies, Informatik 2006Lecture Notes in InformaticsEmergent Semantics in BibSonomyP-9420062006 UniK bibsonomy emergence emergent emergentsemantics_evidence folksonomy hotho itegpub jaeschke l3s nepomuk ol_web2.0 schmitz semantics stumme taggingsurvey tagorapub 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.Fri Jan 28 11:33:17 CET 2011HeidelbergProc. First International Conference on Semantics And Digital Media Technology (SAMT) December56-70LNCSTrend Detection in Folksonomies43062006intranet 2006 trend pagerank hotho schmitz jaeschke l3s itegpub detection triadic stumme nepomuk folksonomy tagorapub folkrank UniK 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.Fri Jul 03 00:09:47 CEST 2009BonnInformatik 2006 -- Informatik für Menschen. Band 2octProc. Workshop on Applications of Semantic Technologies, Informatik 2006Lecture Notes in InformaticsEmergent Semantics in BibSonomyP-9420062006 UniK bibsonomy emergence emergent folksonomy hotho itegpub jaeschke l3s myown nepomuk schmitz semantics stumme tagorapub Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.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.Mon Jan 29 19:11:03 CET 2007HeidelbergProc. First International Conference on Semantics And Digital Media Technology (SAMT) dec56-70LNCSTrend Detection in Folksonomies430620062006 UniK detection folkrank folksonomy hotho intranet itegpub jaeschke l3s myown nepomuk pagerank schmitz stumme tagorapub trend triadic As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.