Sense Induction in Folksonomies

Andrews, Pierre and Pane, Juan and Zaihrayeu, Ilya (2011) Sense Induction in Folksonomies. UNSPECIFIED.

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    Abstract

    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.

    Item Type: Departmental Technical Report
    Department or Research center: Information Engineering and Computer Science
    Subjects: Q Science > QA Mathematics > QA076 Computer software
    Uncontrolled Keywords: folksonomy, semantic, wsd, evaluation, machine learning, clustering
    Additional Information: Also published in: Proceedings of the Workshop on Discovering Meaning on the Go in Large Heterogeneous Data 2011 (LHD-11)
    Report Number: DISI-11-459
    Repository staff approval on: 04 Aug 2011

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