Personalization for Digital Television Using Recommendation System strategy

The increasing content offer and the possibility of new services are two characteristics offered by the digital TV technology (DTV). The personalization is one of these services and it can be a possible solution to the information overload problem caused by the increasing content offer. This amount of information makes difficult the research and localization of interesting content. This paper describes a recommendation system for multi-user environments to offer the personalization. The data mining algorithms from a case study were analyzed in the DTV domain and later a recommendation system was implemented as a concept proof using an API Java TV as a concept proof.