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

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 metada...

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Bibliographic Details
Published in:Multimedia tools and applications 2008, Vol.36 (1-2), p.37-54
Main Authors: Tsunoda, Tomohiro, Hoshino, Masaaki
Format: Article
Language:English
Subjects:
Accuracy
Collaboration
Computer Communication Networks
Computer Science
Customization
Data Structures and Information Theory
Digital video recorders
End users
Internet
Internet appliances
Keywords
Laboratories
Metadata
Methods
Multimedia Information Systems
Preferences
Recommender systems
Special Purpose and Application-Based Systems
Studies
Television programs
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Summary: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.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-006-0077-4