Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: FolkRank: A Ranking Algorithm for Folksonomies. Proc. FGIR 2006. 2006
[Volltext]
In social bookmark tools users are setting up
ghtweight conceptual structures called folksonomies. Currently,
e information retrieval support is limited. We present a formal
del and a new search algorithm for folksonomies, called
lkRank, that exploits the structure of the folksonomy. The
oposed algorithm is also applied to find communities within the
lksonomy and is used to structure search results. All findings are
monstrated on a large scale dataset. A long version of this paper
s been published at the European Semantic Web Conference
06.

Hotho, A.; J?schke, R.; Schmitz, C. & Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y. & Domingue, J. (Hrsg.): The Semantic Web: Research and Applications. Heidelberg: Springer, 2006 (LNAI 4011), S. 411-426

Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking. In: Sure, Y. & Domingue, J. (Hrsg.): The Semantic Web: Research and Applications. Heidelberg: Springer, 2006 (LNAI 4011), S. 411-426

Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: Trend Detection in Folksonomies. In: Avrithis, Y. S.; Kompatsiaris, Y.; Staab, S. & O'Connor, N. E. (Hrsg.): Proc. First International Conference on Semantics And Digital Media Technology (SAMT) . Heidelberg: Springer, 2006 (LNCS 4306), S. 56-70
[Volltext]
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.