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Semantic Measures Based on RDF Projections: Application to Content-Based Recommendation Systems
(Short Paper)
Sébastien Harispe, Sylvie Ranwez, Stefan Janaqi, and Jacky Montmain
LGI2P, Ecole des mines d’Alès, Parc Scientifique G. Besse, F-30035, Nîmes Cedex 1, FranceSebastien.Harispe@mines-ales.fr
Sylvie.Ranwez@mines-ales.fr
Stefan.Janaqi@mines-ales.fr
Jacky.Montmain@mines-ales.fr
Abstract. Many applications take advantage of both ontologies and the Linked Data paradigm to characterize various kinds of resources. To fully exploit this knowledge, measures are used to estimate the relatedness of resources regarding their semantic characterization. Such semantic measures mainly focus on specific aspects of the semantic characterization (e.g. types) or only partially exploit the semantics expressed in the knowledge base. This article presents a framework for defining semantic measures to compare instances defined within an RDF knowledge base. A special type of measure, based on the representation of an instance through projections, is detailed and evaluated through its use in a music band recommender system.
Keywords: Semantic Measures, Semantic similarity/relatedness, RDF Projection, Content-based Recommendation Systems, Similarity between instances
LNCS 8185, p. 606 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2013