Collaborative tagging systems are now popular tools for organising
and sharing information on the Web. While collaborative tagging offers
many advantages over the use of controlled vocabularies, they also
suffer from problems such as the existence of polysemous tags. We
investigate how the different contexts in which individual tags are
used can be revealed automatically without consulting any external
resources. We consider several different network representations
of tags and documents, and apply a graph clustering algorithm on
these networks to obtain groups of tags or documents corresponding
to the different meanings of an ambiguous tag. Our experiments show
that networks which explicitly take the social context into account
are more likely to give a better picture of the semantics of a tag.
%0 Conference Paper
%1 auyeung2009contextualising
%A Au Yeung, Ching Man
%A Gibbins, Nicholas
%A Shadbolt, Nigel
%B Proceedings of the 20th ACM conference on Hypertext and hypermedia
(HT2009)
%C New York, NY, USA
%D 2009
%I ACM
%K diss methods_concepts ol_web2.0 semantics tag
%P 251--260
%R 10.1145/1557914.1557958
%T Contextualising tags in collaborative tagging systems
%X Collaborative tagging systems are now popular tools for organising
and sharing information on the Web. While collaborative tagging offers
many advantages over the use of controlled vocabularies, they also
suffer from problems such as the existence of polysemous tags. We
investigate how the different contexts in which individual tags are
used can be revealed automatically without consulting any external
resources. We consider several different network representations
of tags and documents, and apply a graph clustering algorithm on
these networks to obtain groups of tags or documents corresponding
to the different meanings of an ambiguous tag. Our experiments show
that networks which explicitly take the social context into account
are more likely to give a better picture of the semantics of a tag.
%@ 978-1-60558-486-7
@inproceedings{auyeung2009contextualising,
abstract = {Collaborative tagging systems are now popular tools for organising
and sharing information on the Web. While collaborative tagging offers
many advantages over the use of controlled vocabularies, they also
suffer from problems such as the existence of polysemous tags. We
investigate how the different contexts in which individual tags are
used can be revealed automatically without consulting any external
resources. We consider several different network representations
of tags and documents, and apply a graph clustering algorithm on
these networks to obtain groups of tags or documents corresponding
to the different meanings of an ambiguous tag. Our experiments show
that networks which explicitly take the social context into account
are more likely to give a better picture of the semantics of a tag.},
added-at = {2017-12-10T10:17:41.000+0100},
address = {New York, NY, USA},
author = {{Au Yeung}, Ching Man and Gibbins, Nicholas and Shadbolt, Nigel},
biburl = {https://www.bibsonomy.org/bibtex/29d7b6b68c281a90fc634dc97fc356c96/thoni},
booktitle = {Proceedings of the 20th ACM conference on Hypertext and hypermedia
(HT2009)},
comment = {Contextualising tags in collaborative tagging systems},
doi = {10.1145/1557914.1557958},
file = {auyeung2009contextualising.pdf:auyeung2009contextualising.pdf:PDF},
groups = {friends},
interhash = {3307684746fcac341682e71af32c70bb},
intrahash = {9d7b6b68c281a90fc634dc97fc356c96},
isbn = {978-1-60558-486-7},
keywords = {diss methods_concepts ol_web2.0 semantics tag},
location = {Torino, Italy},
owner = {dbenz},
pages = {251--260},
publisher = {ACM},
timestamp = {2017-12-10T10:18:06.000+0100},
title = {Contextualising tags in collaborative tagging systems},
year = 2009
}