Folksonomies, often known as tagging systems, such as the ones used on the popular Delicious or flickr websites, use a very simple knowledge organisation system.
Users are thus quick to adopt this system and create extensive knowledge annotations on the Web.
However, because of the simplicity of the folksonomy model, the semantics of the tags used is not explicit and can only be inferred from the context of use of the tags.
This is a barrier for the automatic use of such knowledge organisation systems by computers and new techniques have to be developed to extract the semantic of the tags used.
In this paper we discuss an algorithm to detect new senses of terms in a folksonomy; we also propose a formal evaluation methodology that will enable to compare results between different approaches in the field.
This work has been partially supported by INSEMTIVES project (FP7-231181, see http://www.insemtives.eu).
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