Application of Association Rules to User Preference Mining from TV Watching Log and Social Bookmarks

抄録

This paper proposes to apply association rules to user preference mining for TV program recommendation. Transition to digital terrestrial television broadcasting (DTTB) will bring us difficulty in finding TV program worth watching from a number of TV channels. Therefore, a method for recommending TV program will be important in near future. This paper proposes to recommend TV program and related information based on user's TV watching log and social bookmarks. The method represents user's TV watching log with the form of bookmark, which is the same as social bookmarks. Association rules are extracted from the set of bookmarks including TV watching logs and social bookmarks, and extracted rules are used for TV program recommendation. The method is going to be used as one of the modules for realizing Web-based intelligent environment for human-robot casual communication.