M. Grahl, A. Hotho, and G. Stumme. I-KNOW '07. 7th International Conference on Knowledge Management, Graz, Austria, (September 2007)
Abstract
Currently, social bookmarking systems provide intuitive support for
browsing locally their content. A global view is usually presented
by the tag cloud of the system, but it does not allow a conceptual
drill-down, e. g., along a conceptual hierarchy. In this paper, we
present a clustering approach for computing such a conceptual hierarchy
for a given folksonomy. The hierarchy is complemented with ranked
lists of users and resources most related to each cluster. The rankings
are computed using our FolkRank algorithm. We have evaluated our
approach on large scale data from the del.icio.us bookmarking system.
%0 Conference Paper
%1 GrHS07
%A Grahl, Miranda
%A Hotho, Andreas
%A Stumme, Gerd
%B I-KNOW '07. 7th International Conference on Knowledge Management
%C Graz, Austria
%D 2007
%K 2007 DISS bookmarking clustering folkrank folksonomy iknow l3s myown ontologies semantics social tagging tagging_clustering tagging_efficiency tagging_semantics tagora tagorapub toread
%T Conceptual Clustering of Social Bookmarking Sites
%X Currently, social bookmarking systems provide intuitive support for
browsing locally their content. A global view is usually presented
by the tag cloud of the system, but it does not allow a conceptual
drill-down, e. g., along a conceptual hierarchy. In this paper, we
present a clustering approach for computing such a conceptual hierarchy
for a given folksonomy. The hierarchy is complemented with ranked
lists of users and resources most related to each cluster. The rankings
are computed using our FolkRank algorithm. We have evaluated our
approach on large scale data from the del.icio.us bookmarking system.
@inproceedings{GrHS07,
abstract = {Currently, social bookmarking systems provide intuitive support for
browsing locally their content. A global view is usually presented
by the tag cloud of the system, but it does not allow a conceptual
drill-down, e. g., along a conceptual hierarchy. In this paper, we
present a clustering approach for computing such a conceptual hierarchy
for a given folksonomy. The hierarchy is complemented with ranked
lists of users and resources most related to each cluster. The rankings
are computed using our FolkRank algorithm. We have evaluated our
approach on large scale data from the del.icio.us bookmarking system.},
added-at = {2008-01-04T16:59:10.000+0100},
address = {Graz, Austria},
author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/2bf0468ac66e184edc5985fd11654253c/michael},
booktitle = {I-KNOW '07. 7th International Conference on Knowledge Management},
crossref = {@PROCEEDINGS{ToMa07,
title = {Proceedings of I-KNOW 2007},
year = {2007},
editor = {Tochtermann, Klaus and Maurer, Herrmann},
keywords = {knowledgemanagement iknow DISS ownstuff},
timestamp = {2007.11.06}
}},
interhash = {5cf58d2fdd3c17f0b0c54ce098ff5b60},
intrahash = {bf0468ac66e184edc5985fd11654253c},
keywords = {2007 DISS bookmarking clustering folkrank folksonomy iknow l3s myown ontologies semantics social tagging tagging_clustering tagging_efficiency tagging_semantics tagora tagorapub toread},
month = {September},
timestamp = {2008-01-04T16:59:10.000+0100},
title = {Conceptual Clustering of Social Bookmarking Sites},
year = 2007
}