Contextualising tags in collaborative tagging systems Export

@inproceedings{citeulike:5032568, 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.}, address = {New York, NY, USA}, author = {Ching man Au Yeung and Gibbins, Nicholas and Shadbolt, Nigel}, booktitle = {HT '09: Proceedings of the 20th ACM conference on Hypertext and hypermedia}, citeulike-article-id = {5032568}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1557914.1557958}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1557914.1557958}, doi = {10.1145/1557914.1557958}, isbn = {978-1-60558-486-7}, keywords = {ht09, similarity, tagging}, location = {Torino, Italy}, pages = {251--260}, posted-at = {2009-07-01 14:30:46}, priority = {2}, publisher = {ACM}, title = {Contextualising tags in collaborative tagging systems}, url = {http://dx.doi.org/10.1145/1557914.1557958}, year = {2009} }

TY - CONF ID - citeulike:5032568 L3 - citeulike-article-id:5032568 N2 - 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. CY - Torino, Italy SN - 978-1-60558-486-7 AD - New York, NY, USA EP - 260 TI - Contextualising tags in collaborative tagging systems PB - ACM T2 - HT '09: Proceedings of the 20th ACM conference on Hypertext and hypermedia SP - 251 KW - ht09 KW - similarity KW - tagging AU - Ching man Au Yeung AU - Gibbins, Nicholas AU - Shadbolt, Nigel PY - 2009/// UR - http://dx.doi.org/10.1145/1557914.1557958 ER -