Organizing Resources on Tagging Systems using T-ORG
R. Abbasi, S. Staab, and P. Cimiano. Bridging the Gep between Semantic Web and Web 2.0 (SemNet 2007), page 97-110. (2007)
Abstract
Tagging systems (or folksonomies) like Flickr or Delicious are
expanding tremendously. More and more resources are being added to them. As
the resources present on these system increase in amount, it becomes difficult to
explore these resources. For this purpose, we present a system T-ORG, which
provides a mechanism to organize these resources by classifying the tags (or
keywords) attached to them into predefined categories. Supervised
classification in this case seems infeasible; therefore we also propose a new
classification algorithm T-KNOW that does not require training data. For our
experiments, we have downloaded images and their tags from groups present on
Flickr website and then classified these tags into different categories. We have
used Cohen’s Kappa and F-measure to evaluate the classification results of T-
KNOW. Results are encouraging and show that T-ORG can be used to explore
resources in an effective manner.
%0 Conference Paper
%1 Abbasi:2007
%A Abbasi, Rabeeh
%A Staab, Steffen
%A Cimiano, Philipp
%B Bridging the Gep between Semantic Web and Web 2.0 (SemNet 2007)
%D 2007
%K Classification Folksonomies Semantic Systems Tagging Tags Web
%P 97-110
%T Organizing Resources on Tagging Systems using T-ORG
%U http://www.kde.cs.uni-kassel.de/ws/eswc2007/proc/OrganizingResources.pdf
%X Tagging systems (or folksonomies) like Flickr or Delicious are
expanding tremendously. More and more resources are being added to them. As
the resources present on these system increase in amount, it becomes difficult to
explore these resources. For this purpose, we present a system T-ORG, which
provides a mechanism to organize these resources by classifying the tags (or
keywords) attached to them into predefined categories. Supervised
classification in this case seems infeasible; therefore we also propose a new
classification algorithm T-KNOW that does not require training data. For our
experiments, we have downloaded images and their tags from groups present on
Flickr website and then classified these tags into different categories. We have
used Cohen’s Kappa and F-measure to evaluate the classification results of T-
KNOW. Results are encouraging and show that T-ORG can be used to explore
resources in an effective manner.
@inproceedings{Abbasi:2007,
abstract = {Tagging systems (or folksonomies) like Flickr or Delicious are
expanding tremendously. More and more resources are being added to them. As
the resources present on these system increase in amount, it becomes difficult to
explore these resources. For this purpose, we present a system T-ORG, which
provides a mechanism to organize these resources by classifying the tags (or
keywords) attached to them into predefined categories. Supervised
classification in this case seems infeasible; therefore we also propose a new
classification algorithm T-KNOW that does not require training data. For our
experiments, we have downloaded images and their tags from groups present on
Flickr website and then classified these tags into different categories. We have
used Cohen’s Kappa and F-measure to evaluate the classification results of T-
KNOW. Results are encouraging and show that T-ORG can be used to explore
resources in an effective manner.},
added-at = {2007-06-03T15:07:34.000+0200},
author = {Abbasi, Rabeeh and Staab, Steffen and Cimiano, Philipp},
biburl = {https://www.bibsonomy.org/bibtex/2e4d7cbfa0708c70987eade1cb406f2e5/daill},
booktitle = {Bridging the Gep between Semantic Web and Web 2.0 (SemNet 2007)},
interhash = {a81bff4d79a45840a0abca9ef4468fb0},
intrahash = {e4d7cbfa0708c70987eade1cb406f2e5},
keywords = {Classification Folksonomies Semantic Systems Tagging Tags Web},
pages = {97-110},
timestamp = {2007-06-03T15:07:34.000+0200},
title = {Organizing Resources on Tagging Systems using T-ORG},
url = {http://www.kde.cs.uni-kassel.de/ws/eswc2007/proc/OrganizingResources.pdf},
year = 2007
}