C. Schmitz, A. Hotho, R. Jäschke, и G. Stumme. Data Science and Classification. Proceedings of the 10th IFCS Conf., стр. 261--270. Heidelberg, Springer, (июля 2006)
Аннотация
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 Schmitz_et_al_2006
%A Schmitz, Christoph
%A Hotho, Andreas
%A Jäschke, Robert
%A Stumme, Gerd
%B Data Science and Classification. Proceedings of the 10th IFCS Conf.
%C Heidelberg
%D 2006
%E Batagelj, V.
%E Bock, H.-H.
%E Ferligoj, A.
%E Žiberna, A.
%I Springer
%K 2006 ezweb folksonomy ontology
%P 261--270
%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.
@inproceedings{Schmitz_et_al_2006,
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 = {2007-11-10T17:31:55.000+0100},
address = {Heidelberg},
author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/211b2a59a568d246d7f36cb68169a464a/berrueta},
booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.},
editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and Žiberna, A.},
interhash = {20650d852ca3b82523fcd8b63e7c12d7},
intrahash = {11b2a59a568d246d7f36cb68169a464a},
keywords = {2006 ezweb folksonomy ontology},
month = {July},
pages = {261--270},
publisher = {Springer},
series = {Studies in Classification, Data Analysis, and Knowledge Organization},
timestamp = {2007-11-10T20:00:51.000+0100},
title = {Mining Association Rules in Folksonomies},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf},
year = 2006
}