Estimation of user preference for TV programs based on channel operations

Abstract

We propose estimation technique of user preferences for TV programs based on channel operations. The user preferences are available for automatic recommendation of TV programs. For practical use, automatically learning the preferences of a user from a channel selection history is important. However, obtaining such information is difficult because most users change channels frequently and do not watch programs from beginning to end. For automatic learning under such situations, an appropriate hypothesis describing the relationship between viewing time and preference degree for a program is needed. We propose three hypotheses and compared their utility in our program recommendation system. Experimental results showed that the preference for a TV program is not proportional to the viewing time, but becomes either 1 (like) or 0 (dislike) about 30 minutes after channel selection.