Employing User-Generated Tags to Provide Personalized as well as Collaborative TV Recommendations

Within the Web, the annotation of content has become a common way to provide efficient navigation and recommendation of resources. In the future, TV sets with integrated Web capabilities will offer tagging as a tool for content organization in the realm of home entertainment. The recommendation of TV content is a challenging task as a system has to consider each user’s individual preferences without getting too specific. We present a strategy which employs user-generated tags in a flexible way to address this issue. Our approach provides two different ways of semantic ranking for TV program lists: The first allows a higher ranking of programs that fit well to the user’s personal likings. The second introduces collaborative aspects and therefore promotes a community-driven approach rather than an individual way of recommendation.