A SEMANTIC APPROACH FOR RECOMMENDATIONS GENERATION: SOME CULTURAL HERITAGE APPLICATIONS

The growing availability of data in the information systems has raised the challenging problem of distinguishing between the resources that belong to the same information context. Starting from the hypothesis that the information system is based on Semantic Web technologies, is it possible to use these technologies to make an information system more adaptive to user requirements in order to enable personalization and differentiation mechanisms in the information delivery process? This paper proposes an approach to building recommendations by using Semantic Web technologies, in order to give the users a different access to the information. The outcome is a semantic recommender engine, capable of retrieving and ranking semantically annotated resources, by using a set of domain ontologies and a semantic matching algorithm. We are showing some applications of this model in the Cultural Heritage domain in which the presented approach seems to be particularly effective, due to the richness of semantic structures and models existing for such domain.