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Exploring the Semantic Web as Background Knowledge for Ontology Matching
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The Semantic Web community has expressed its interest on how the Semantic Web technology can be applied more efficiently in a manner that supports real world applications. Additionally, the popularity of social tagging systems has demonstrated a clear need for organisation and more flexible ways of querying the user contributed content. This work presents FLOR, a folksonomy enrichment algorithm, which exploits a variety of knowledge sources to apply structure on the user tagspaces. In addition, a query mechanism is presented demonstrating how the enriched folksonomies structures can be interrogated by transforming the user keyword queries on folksonomies to formal queries on semantic structures. The first prototype of the FLOR enrichment algorithm and a first instance of the query mechanism have been implemented and a demonstration is available online.