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Automatic metadata expansion and indirect collaborative filtering for TV program recommendation system

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Abstract

TV Program recommendation is a good example of a novel application of networked appliances using personalization technologies. The aim of this paper is to propose methods to improve the accuracy of TV program recommendation. Automatic metadata expansion (AME) is a method to enhance TV program metadata from electronic program guide (EPG) data, and indirect collaborative filtering (ICF) is a method to recommend non-persistent items such as TV programs based on the preferences of other members in a community. In this paper, the effectiveness of these methods is confirmed through experiments. This online TV recommendation system is currently being used by 230,000 members in Japan. The result of the actual operation is also discussed.

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Authors and Affiliations

  1. PAO Group, Intelligent Systems Research Laboratory, Information Technologies Laboratories, Sony Corporation, Tokyo, Japan

    Tomohiro Tsunoda & Masaaki Hoshino

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  1. Tomohiro Tsunoda
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  2. Masaaki Hoshino
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Correspondence to Tomohiro Tsunoda.

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Tsunoda, T., Hoshino, M. Automatic metadata expansion and indirect collaborative filtering for TV program recommendation system. Multimed Tools Appl 36, 37–54 (2008). https://doi.org/10.1007/s11042-006-0077-4

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  • DOI: https://doi.org/10.1007/s11042-006-0077-4

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