Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.
%0 Journal Article
%1 Jaeschke_et_al_2008
%A Jäschke, Robert
%A Hotho, Andreas
%A Schmitz, Christoph
%A Ganter, Bernhard
%A Stumme, Gerd
%B Semantic Web and Web 2.0
%C New York
%D 2008
%E Finin, T.
%E Mizoguchi, R.
%E Staab, S.
%I Elsevier
%J Web Semantics: Science, Services and Agents on the World Wide Web
%K analysis emergent_semantics folksonomy my_thesis ontology
%N 1
%P 38--53
%R 10.1016/j.websem.2007.11.004
%T Discovering Shared Conceptualizations in Folksonomies
%U http://www.sciencedirect.com/science/article/B758F-4R53WD4-1/2/ae56bd6e7132074272ca2035be13781b
%V 6
%X Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.
@article{Jaeschke_et_al_2008,
abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.},
added-at = {2011-01-10T19:07:33.000+0100},
address = {New York},
author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/218e8babe208fae2c0342438617b0ec31/bluedolphin},
booktitle = {Semantic Web and Web 2.0},
doi = {10.1016/j.websem.2007.11.004},
editor = {Finin, T. and Mizoguchi, R. and Staab, S.},
interhash = {cfca594f9dbe30694bfbcdeb40dc4e88},
intrahash = {18e8babe208fae2c0342438617b0ec31},
issn = {1570-8268},
journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
keywords = {analysis emergent_semantics folksonomy my_thesis ontology},
month = feb,
number = 1,
pages = {38--53},
publisher = {Elsevier},
timestamp = {2011-01-10T19:07:33.000+0100},
title = {Discovering Shared Conceptualizations in Folksonomies},
url = {http://www.sciencedirect.com/science/article/B758F-4R53WD4-1/2/ae56bd6e7132074272ca2035be13781b},
volume = 6,
year = 2008
}