Enhancing Folksonomy-Based Content Retrieval with Semantic Web Technology

While Flickr, a widely-known photo sharing system, allows users to describe their own photos with tags aka. folksonomy tags for indexing purposes, its tag-based photo retrieval function is severely hampered by the inherent nature of folksonomy tags. This paper presents SemFlickr, an application which enhances the search in Flickr with its semantic query suggestion feature. SemFlickr employs SQORE, an ontology retrieval system, to retrieve relevant ontologies from the Semantic Web and then derives query term suggestions from those ontologies. To ensure that the highly related photos will appear at the top of the results, SemFlickr takes the ontological relations among the given query terms to assign tag scores and then generates its ranked results. Experimental outcomes are encouraging and reveal a number of useful insights for developing applications that integrate the Semantic Web and Web 2.0 together.

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