An automatic classification system for consumer regulatory focus by analyzing web shopping logs
Proceedings of the 2012 ACM Research in Applied Computation Symposium
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Mobile TV provides multimedia contents to the user by wireless communication. Here the personalized recommendation system allows the users to easily select the contents wanting to access. In this paper we propose a personalized recommendation scheme which considers the activities of the user at runtime and the information on the environment around the user. It allows efficient operation in mobile device, and interoperability between the TV multimedia metadata and ontology. The accuracy of the proposed scheme is evaluated by an experiment, which reveals a significant improvement compared to the existing schemes.