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

Shunichi Hattori; Yoshihiro Iwase; Yuki Muto; Yasufumi Takama

doi:10.14864/softscis.2006.0.430.0

SCIS & ISIS 2006

Session ID : TH-H3-3

DOI https://doi.org/10.14864/softscis.2006.0.430.0

Conference information

Host: Japan SOciety for Fuzzy Theory and intelligent informatics

Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

TH-H3 Humatronics Concept on Robot Technology

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

*Shunichi Hattori, Yoshihiro Iwase, Yuki Muto, Yasufumi Takama

Author information

Keywords: human-robot communication, association rule, information filtering

CONFERENCE PROCEEDINGS FREE ACCESS

Details

Abstract

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.

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