An Adaptive Cartography of DTV Programs
EUROITV '08 Proceedings of the 6th European conference on Changing Television Environments
Receiver-side semantic reasoning for digital TV personalization in the absence of return channels
Multimedia Tools and Applications
Exploring synergies between digital tv recommender systems and electronic health records
Proceedings of the 8th international interactive conference on Interactive TV&Video
Information Sciences: an International Journal
Property-based collaborative filtering for health-aware recommender systems
Expert Systems with Applications: An International Journal
Using control theory for stable and efficient recommender systems
Proceedings of the 21st international conference on World Wide Web
Intelligent media indexing and television recommender systems
FDIA'09 Proceedings of the Third BCS-IRSG conference on Future Directions in Information Access
An approach for T-learning content generation based on a social media environment
Proceedings of the 10th European conference on Interactive tv and video
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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.