A Recommendation System for the Semantic Web [chapter]

Victor Codina, Luigi Ceccaroni
2010 Advances in Intelligent and Soft Computing  
Recommendation systems can take advantage of semantic reasoningcapabilities to overcome common limitations of current systems and improve the recommendations' quality. In this paper, we present a personalizedrecommendation system, a system that makes use of representations of items and user-profiles based on ontologies in order to provide semantic applications with personalized services. The recommender uses domain ontologies to enhance the personalization: on the one hand, user's interests are
more » ... modeled in a more effective and accurate way by applying a domain-based inference method; on the other hand, the matching algorithm used by our content-based filtering approach, which provides a measure of the affinity between an item and a user, is enhanced by applying a semantic similarity method. The experimental evaluation on the Netflix movie-dataset demonstrates that the additional knowledge obtained by the semantics-based methods of the recommender contributes to the improvement of recommendation's quality in terms of accuracy.
doi:10.1007/978-3-642-14883-5_6 dblp:conf/dcai/CodinaC10 fatcat:5zkhekfknfheppqdikmphbwhw4