Position Paper: Ontology Learning from Folksonomies
D. Benz, and A. Hotho. Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007), page 109--112. Martin-Luther-Universität Halle-Wittenberg, (September 2007)http://lwa07.informatik.uni-halle.de/kdml07/kdml07.htm.
Abstract
The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussing on a formal description and analysis of the resulting “folksonomies�?. An interesting outcome is that the characteristic qualities of these systems seem to be inverse to more traditional knowledge structuring approaches like taxonomies or ontologies: The latter provide rich and precise semantics, but suffer - amongst others - from a knowledge acquisition bottleneck. An important step towards exploiting the possible synergies by bridging the gap between both paradigms is the automatic extraction of relations between tags in a folksonomy. This position paper presents preliminary results of ongoing work to induce hierarchical relationships among tags by analyzing the aggregated data of collaborative tagging systems as a basis for an ontology learning procedure.
%0 Conference Paper
%1 benz2007position
%A Benz, Dominik
%A Hotho, Andreas
%B Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)
%D 2007
%E Hinneburg, Alexander
%I Martin-Luther-Universität Halle-Wittenberg
%K 2007 diploma_thesis ibm-kde-tagging itegpub methods_concepthierarchy myown ol_web2.0 ontology_learning rel1 rel2 taggingsurvey tagorapub
%P 109--112
%T Position Paper: Ontology Learning from Folksonomies
%U http://www.kde.cs.uni-kassel.de/pub/pdf/benz2007position.pdf
%X The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussing on a formal description and analysis of the resulting “folksonomies�?. An interesting outcome is that the characteristic qualities of these systems seem to be inverse to more traditional knowledge structuring approaches like taxonomies or ontologies: The latter provide rich and precise semantics, but suffer - amongst others - from a knowledge acquisition bottleneck. An important step towards exploiting the possible synergies by bridging the gap between both paradigms is the automatic extraction of relations between tags in a folksonomy. This position paper presents preliminary results of ongoing work to induce hierarchical relationships among tags by analyzing the aggregated data of collaborative tagging systems as a basis for an ontology learning procedure.
%@ 978-3-86010-907-6
@inproceedings{benz2007position,
abstract = {The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussing on a formal description and analysis of the resulting “folksonomies�?. An interesting outcome is that the characteristic qualities of these systems seem to be inverse to more traditional knowledge structuring approaches like taxonomies or ontologies: The latter provide rich and precise semantics, but suffer - amongst others - from a knowledge acquisition bottleneck. An important step towards exploiting the possible synergies by bridging the gap between both paradigms is the automatic extraction of relations between tags in a folksonomy. This position paper presents preliminary results of ongoing work to induce hierarchical relationships among tags by analyzing the aggregated data of collaborative tagging systems as a basis for an ontology learning procedure.},
added-at = {2011-02-17T17:41:38.000+0100},
author = {Benz, Dominik and Hotho, Andreas},
biburl = {https://www.bibsonomy.org/bibtex/272bff5ebe5dfb5023f62ba9b94e6ed01/dbenz},
booktitle = {Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)},
editor = {Hinneburg, Alexander},
file = {benz2007position.pdf:benz2007position.pdf:PDF},
groups = {public},
interhash = {ff7de5717f771dabd764675279ff3adf},
intrahash = {72bff5ebe5dfb5023f62ba9b94e6ed01},
isbn = {978-3-86010-907-6},
keywords = {2007 diploma_thesis ibm-kde-tagging itegpub methods_concepthierarchy myown ol_web2.0 ontology_learning rel1 rel2 taggingsurvey tagorapub},
month = sep,
note = {http://lwa07.informatik.uni-halle.de/kdml07/kdml07.htm},
pages = {109--112},
publisher = {Martin-Luther-Universität Halle-Wittenberg},
timestamp = {2013-07-31T15:39:42.000+0200},
title = {Position Paper: Ontology Learning from Folksonomies},
url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2007position.pdf},
username = {dbenz},
year = 2007
}