Contextualising Tags in Collaborative Tagging Systems
C. man Au Yeung, N. Gibbins, und N. Shadbolt. HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia, New York, NY, USA, ACM, (Juli 2009)
Zusammenfassung
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 yeung09contextualising
%A man Au Yeung, Ching
%A Gibbins, Nicholas
%A Shadbolt, Nigel
%B HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia
%C New York, NY, USA
%D 2009
%I ACM
%K research.web20.tagging research.conceptual.folksonomy
%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.
@inproceedings{yeung09contextualising,
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 = {2010-10-07T12:19:32.000+0200},
address = {New York, NY, USA},
author = {man Au Yeung, Ching and Gibbins, Nicholas and Shadbolt, Nigel},
biburl = {https://www.bibsonomy.org/bibtex/2f3000777d9b48c7a5e7499def8e45e8e/msn},
booktitle = {HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia},
interhash = {f1e4766edac9ec9545c866fda9fa2a4c},
intrahash = {f3000777d9b48c7a5e7499def8e45e8e},
keywords = {research.web20.tagging research.conceptual.folksonomy},
month = {July},
paperid = {fp017},
publisher = {ACM},
session = {Full Paper},
timestamp = {2010-10-07T12:19:33.000+0200},
title = {Contextualising Tags in Collaborative Tagging Systems},
year = 2009
}