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.
Users
Please
log in to take part in the discussion (add own reviews or comments).