Experiences in Using Semantic Technologies for Providing Added‐Value Services in DigitalTV

Abstract

Interactive digital TV ( IDTV ) has changed the traditional perception people used to have about audiovisual content consumption. The merely passive viewers are adopting active roles by interacting with the applications that are broadcast over the IDTV networks. Besides, the great amount of broadcast information (audiovisual and applications) opens new possibilities for the audience, who has a broader bouquet of content to explore. However, and overwhelmed by the filtering process, users need a service to help them to decide what to watch. At this point, we propose to apply semantic tecniques to improve the filtering tasks and so, the experiences described in this chapter have the semantic TV content recommender that we have developed, AVATAR , as base for offering new serviced to the TV audience: advertising techniques, t‐learning, and adopting special solutions for the TV on the move.