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AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning

, , , , , , , , and . Lecture Notes Computer Science, (2004)(Web Information Systems – WISE 2004).

Abstract

In this paper a recommender system of personalized TV contents, named AVATARWork supported by the Ministerio de Educación y Ciencia Research Project TSI2004-03677., is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies – more specifically an OWL ontology – and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators. ER -

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