A Parametric Architecture for Tags Clustering in Folksonomic Search Engines

Semantic search engines rely on the existence of a rich set of semantic connections between the concepts associated to documents and those used for the queries. With folksonomies, this is not always guaranteed. Creating clusters of folksonomic tags around terms of controlled ontological vocabularies is a potentially sophisticated approach, but algorithms abound for this clustering and no clear cut winner exists. In this paper we introduce FolksEngine, a parametric search engine for folksonomies allowing to specify any clustering algorithm as a three step process: the user’s query is expanded according to semantic rules associated to the terms of the query, the new query is then executed on the plain folksonomy search engine, and the results are ranked according to semantic rules associated to the folksonomic tags actually used for the documents.