Abstract
In this chapter, we provide techniques for automatically classifying and coordinating tags extracted from one or more folksonomies, with the aim of building collective tag intelligence which can then be exploited to improve the conventional searching functionalities provided by tagging systems. Collective tag intelligence is organized in form of tag equivalence clusters with corresponding semantic, terminological, and linguistic relations. For building tag collective intelligence, we define i) normalization techniques to identify equivalence clusters of tags and extract the relations holding between them and ii) similarity techniques to match tags on the basis of available collective tag intelligence. Finally, we describe the evaluation of the proposed techniques over real datasets extracted from del.icio.us and Flickr folksonomies and a real application example of exploiting the collective tag intelligence for similarity-based resource retrieval.
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Varese, G., Castano, S. (2011). Building Collective Tag Intelligence through Folksonomy Coordination. In: Bessis, N., Xhafa, F. (eds) Next Generation Data Technologies for Collective Computational Intelligence. Studies in Computational Intelligence, vol 352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20344-2_4
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DOI: https://doi.org/10.1007/978-3-642-20344-2_4
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