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 J�schke, 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 = {2011-06-10T09:04:03.000+0200},
address = {New York},
author = {J�schke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/29ee9510a1d4d5acdcd85a4e005ea059b/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 = {eaa6ccd41a120c92706096ec3916db97},
intrahash = {9ee9510a1d4d5acdcd85a4e005ea059b},
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 = {2011-06-10T09:04:08.000+0200},
title = {Discovering Shared Conceptualizations in Folksonomies},
url = {http://www.sciencedirect.com/science/article/B758F-4R53WD4-1/2/ae56bd6e7132074272ca2035be13781b},
volume = 6,
year = 2008
}