Computational and crowdsourcing methods for extracting ontological structure from folksonomy

Abstract

This paper investigates the unification of folksonomies and ontologies in such a way that the resulting structures can better support exploration and search on the World Wide Web. First, an integrated computational method is employed to extract the ontological structures from folksonomies. It exploits the power of low support association rule mining supplemented by an upper ontology such as WordNet. Promising results have been obtained from experiments using tag datasets from Flickr and Citeulike. Next, a crowdsourcing method is introduced to channel online users' search efforts to help evolve the extracted ontology. © 2010 Springer-Verlag.