Social bookmark tools are rapidly emerging on the Web. In such
systems users are setting up lightweight conceptual structures
called folksonomies. These systems provide currently relatively few
structure. We discuss in this paper, how association rule mining
can be adopted to analyze and structure folksonomies, and how the results can be used
for ontology learning and supporting emergent semantics. We
demonstrate our approach on a large scale dataset stemming from an
online system.
%0 Conference Paper
%1 schmitz2006mining
%A Schmitz, Christoph
%A Hotho, Andreas
%A Jäschke, Robert
%A Stumme, Gerd
%B Data Science and Classification
%C Berlin/Heidelberg
%D 2006
%E Batagelj, V.
%E Bock, H.-H.
%E Ferligoj, A.
%E Žiberna, A.
%I Springer
%K 2006 association folksonomy iccs_example l3s mining myown ol_tut2010 rule trias_example
%P 261--270
%R 10.1007/3-540-34416-0_28
%T Mining Association Rules in Folksonomies
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf
%X Social bookmark tools are rapidly emerging on the Web. In such
systems users are setting up lightweight conceptual structures
called folksonomies. These systems provide currently relatively few
structure. We discuss in this paper, how association rule mining
can be adopted to analyze and structure folksonomies, and how the results can be used
for ontology learning and supporting emergent semantics. We
demonstrate our approach on a large scale dataset stemming from an
online system.
%Z Proc. of the 10th IFCS Conf.
%@ 978-3-540-34415-5
@inproceedings{schmitz2006mining,
abstract = {Social bookmark tools are rapidly emerging on the Web. In such
systems users are setting up lightweight conceptual structures
called folksonomies. These systems provide currently relatively few
structure. We discuss in this paper, how association rule mining
can be adopted to analyze and structure folksonomies, and how the results can be used
for ontology learning and supporting emergent semantics. We
demonstrate our approach on a large scale dataset stemming from an
online system.},
added-at = {2007-02-01T14:04:37.000+0100},
address = {Berlin/Heidelberg},
annote = {Proc. of the 10th IFCS Conf.},
author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/27f502f47bd0e584190337e3e2d4eba9e/jaeschke},
booktitle = {Data Science and Classification},
doi = {10.1007/3-540-34416-0_28},
editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and Žiberna, A.},
interhash = {20650d852ca3b82523fcd8b63e7c12d7},
intrahash = {7f502f47bd0e584190337e3e2d4eba9e},
isbn = {978-3-540-34415-5},
keywords = {2006 association folksonomy iccs_example l3s mining myown ol_tut2010 rule trias_example},
pages = {261--270},
publisher = {Springer},
series = {Studies in Classification, Data Analysis, and Knowledge Organization},
timestamp = {2017-07-05T14:54:07.000+0200},
title = {Mining Association Rules in Folksonomies},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf},
year = 2006
}