The State of the Art in Tag Ontologies: A Semantic Model for Tagging and Folksonomies

Hak Lae Kim, Simon Scerri, John G. Breslin, Stefan Decker, Hong Gee Kim

Abstract


There is a growing interest on how we represent and share
tagging data for the purpose of collaborative tagging systems. Conventional tags,
however, are not naturally suited for collaborative processes. Being free-text
keywords, they are exposed to linguistic variations like case (upper vs lower),
grammatical number (singular vs. plural) as well as human typing errors.
Additionally, tags depend on the personal views of the world by individual users,
and are not normalized for synonymy, morphology or any other mapping. The bottom
line of the problem is that tags have no semantics whatsoever. Moreover, even if a
user gives some semantics to a tag while using or viewing it, this meaning is not
automatically shared with computers since it’s not defined in a machine-readable
way. With tagging systems increasing in popularity each day, the evolution of this
technology is hindered by this problem. In this paper we discuss approaches to
represent tagging activities at a semantic level. We present criteria for the
comparison of existing tag ontologies and discuss their strengths and weaknesses in
relation to these criteria.

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