AVATAR: an approach based on semantic reasoning to recommend personalized TV programs

ABSTRACT

In this paper a TV recommender system called AVATAR (AdVAnce Telematic search of Audiovisual contents by semantic Reasoning) is presented. This tool uses the experience gained in the field of the Semantic Web to personalize the TV programs shown to the end users. The main contribution of our system is a process of semantic reasoning carried out on the descriptions of the TV contents ---provided by means of metainformation--- and on the viewer preferences --- contained in personal profiles. Such process allows to diversify the offered suggestions maintaining the personalization, given that the aim is to find contents appealing for the users, which are related semantically to their programs of interest.Here the framework proposed for this reasoning is introduced, by including (i) the OWL ontology chosen to represent the knowledge of our application domain, (ii) the organization of the user profiles, (iii) the query language LIKO, which is intended to browse the ontology and (iv) the semantic relations inferred from the system knowledge base.

REFERENCES

• 1: V. Geroimenko and C. Chen. Visualizing the Semantic Web. Springer Verlag, 2003.
• 2: Y. Blanco, J. J. Pazos, A. Gil, M. Ramos, A. Fernández, R. P. Díaz, M. López and B. Barragáns. AVATAR: An advanced Multi-Agent Recommender System of Personalized TV Contents by Semantic Reasoning. In Proceedings of 5th International Conference on Web Information Systems Engineering, volume 3306 of Lectures Notes in Computer Science, pages 415--421. Springer-Verlag, 2004.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

General Terms:
Languages, Management, Theory

Keywords:
TV recommender system, inference of semantic relations, ontologies, semantic web