TY - CONF AU - Hotho, Andreas AU - Jäschke, Robert AU - Schmitz, Christoph AU - Stumme, Gerd A2 - Hochberger, Christian A2 - Liskowsky, Rüdiger T1 - Emergent Semantics in BibSonomy T2 - Informatik 2006 -- Informatik für Menschen. Band 2 PB - Gesellschaft für Informatik CY - Bonn PY - 2006/october M2 - VL - P-94 IS - SP - EP - UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf M3 - KW - 2006 KW - UniK KW - bibsonomy KW - emergence KW - emergent KW - folksonomy KW - hotho KW - itegpub KW - jaeschke KW - l3s KW - nepomuk KW - schmitz KW - semantics KW - stumme KW - tagorapub KW - ol_web2.0 KW - emergentsemantics_evidence L1 - SN - N1 - N1 - AB - 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. 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 -