The growing popularity of social tagging systems promises to alleviate the knowledge bottleneck that slows the full materialization of the Semantic Web, as these systems are cheap, extendable, scalable and respond quickly to user needs. However, for the sake of knowledge workflow, one needs to find a compromise between the ungoverned nature of folksonomies and the controlled vocabulary of domain-experts. In this paper, we address this concern by first devising a method that automatically combines folksonomies with domain-expert ontologies resulting in an enriched folksonomy. We then introduce a new algorithm based on frequent itemsets mining that efficiently learns an ontology over the concepts present in the enriched folksonomy. Moreover, we propose a new benchmark for ontology evaluation, which is used in the context of information finding, since this is one of the leading motivations for using ontologies in social tagging systems, to quantitatively assess our method. We conduct experiments on real data and empirically show the effectiveness of our approach.
Topicmaps.Org is an independent consortium of parties interested in developing the applicability of the Topic Maps Paradigm[1] to the World Wide Web, by leveraging the XML family of specifications as required.
This work includes the development of version 1.0 of an XML grammar for interchanging Web-based Topic Maps, called XML Topic Maps (XTM) Version 1.0, written by the Topicmaps.Org Authoring Group. All versions of the XTM Specification will be permanently licensed to the public.
Automatic semantic annotation of information content is an open problem, but is crucial to the realization of the Semantic Web. Annotation systems require the initial definition of an ontology and as well as a knowledge base. Both of these resources work
Automatic semantic annotation of information content is an open problem, but is crucial to the realization of the Semantic Web. Annotation systems require the initial definition of an ontology and as well as a knowledge base. Both of these resources work
M. Magableh, A. Cau, H. Zedan, und M. Ward. Proceedings of the IADIS International Conferences Collaborative Technologies 2010 and Web Based Communities 2010, Seite 178--182. (Juli 2010)