A TV-anytime metadata approach to TV program recommendation for groups

The advent of digital TV and personal digital recorders promise to change the way people watch TV. The higher efficiency of digital coding will lead to increasing the number of contents offered to the user, demanding automatic tools for content recommendation. In the other hand, digital recorders will permit a non-linear consumption model, enabling the creation of (automatic) personalized schedules that combine the appealing contents for a concrete user. This paper presents a semantic approach to content recommendation for groups of people, starting from TV-anytime descriptions of the contents to be broadcast.