TY - CONF AU - Hotho, Andreas AU - Jäschke, Robert AU - Schmitz, Christoph AU - Stumme, Gerd A2 - T1 - Das Entstehen von Semantik in BibSonomy T2 - Social Software in der Wertschöpfung PB - Nomos CY - Baden-Baden PY - 2006/ M2 - VL - IS - SP - EP - UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006entstehen.pdf M3 - KW - tags KW - semantik KW - 2006 KW - pagerank KW - tagging KW - association KW - hotho KW - bibsonomy KW - schmitz KW - jaeschke KW - rules KW - semantics KW - stumme KW - BibSonomy KW - nepomuk KW - folksonomy KW - tagorapub KW - folksonomies KW - tagora KW - folkrank KW - UniK KW - ol_web2.0 KW - emergentsemantics_evidence L1 - E:\home\help_of_all_helps.pdf SN - N1 - N1 - AB - 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. ER - TY - CONF AU - Hotho, Andreas AU - Jäschke, Robert AU - Schmitz, Christoph AU - Stumme, Gerd A2 - T1 - FolkRank: A Ranking Algorithm for Folksonomies T2 - Proc. FGIR 2006 PB - CY - PY - 2006/ M2 - VL - IS - SP - EP - UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf M3 - KW - 2006 KW - algorithm KW - folkrank KW - ir KW - itegpub KW - l3s KW - myown KW - nepomuk KW - pagerank KW - ranking L1 - SN - N1 - N1 - AB - In social bookmark tools users are setting up

lightweight conceptual structures called folksonomies. Currently,

the information retrieval support is limited. We present a formal

model and a new search algorithm for folksonomies, called

FolkRank, that exploits the structure of the folksonomy. The

proposed algorithm is also applied to find communities within the

folksonomy and is used to structure search results. All findings are

demonstrated on a large scale dataset. A long version of this paper

has been published at the European Semantic Web Conference

2006. ER - TY - CONF AU - Hotho, Andreas AU - Jäschke, Robert AU - Schmitz, Christoph AU - Stumme, Gerd A2 - T1 - FolkRank: A Ranking Algorithm for Folksonomies T2 - Proc. FGIR 2006 PB - CY - PY - 2006/ M2 - VL - IS - SP - EP - UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf M3 - KW - 2006 KW - algorithm KW - folkrank KW - ir KW - itegpub KW - l3s KW - myown KW - nepomuk KW - pagerank KW - ranking L1 - SN - N1 - Publications of Gerd Stumme N1 - AB - In social bookmark tools users are setting up

lightweight conceptual structures called folksonomies. Currently,

the information retrieval support is limited. We present a formal

model and a new search algorithm for folksonomies, called

FolkRank, that exploits the structure of the folksonomy. The

proposed algorithm is also applied to find communities within the

folksonomy and is used to structure search results. All findings are

demonstrated on a large scale dataset. A long version of this paper

has been published at the European Semantic Web Conference

2006. ER - TY - CONF AU - Hotho, Andreas AU - Jäschke, Robert AU - Schmitz, Christoph AU - Stumme, Gerd A2 - Avrithis, Yannis S. A2 - Kompatsiaris, Yiannis A2 - Staab, Steffen A2 - O'Connor, Noel E. T1 - Trend Detection in Folksonomies T2 - Proc. First International Conference on Semantics And Digital Media Technology (SAMT) PB - Springer CY - Heidelberg PY - 2006/12 M2 - VL - 4306 IS - SP - 56 EP - 70 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf M3 - KW - 2006 KW - UniK KW - detection KW - folkrank KW - folksonomy KW - hotho KW - intranet KW - itegpub KW - jaeschke KW - l3s KW - myown KW - nepomuk KW - pagerank KW - schmitz KW - stumme KW - tagorapub KW - trend KW - triadic L1 - SN - 3-540-49335-2 N1 - N1 - AB - 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. ER - TY - CONF AU - Hotho, Andreas AU - Jäschke, Robert AU - Schmitz, Christoph AU - Stumme, Gerd A2 - Avrithis, Yannis S. A2 - Kompatsiaris, Yiannis A2 - Staab, Steffen A2 - O'Connor, Noel E. T1 - Trend Detection in Folksonomies T2 - Proc. First International Conference on Semantics And Digital Media Technology (SAMT) PB - Springer CY - Heidelberg PY - 2006/12 M2 - VL - 4306 IS - SP - 56 EP - 70 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006trend.pdf M3 - KW - intranet KW - 2006 KW - trend KW - pagerank KW - hotho KW - schmitz KW - jaeschke KW - l3s KW - itegpub KW - detection KW - triadic KW - stumme KW - nepomuk KW - folksonomy KW - tagorapub KW - folkrank KW - UniK L1 - SN - 3-540-49335-2 N1 - N1 - AB - 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. ER -