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  -