Receiver-side semantic reasoning for digital TV personalization in the absence of return channels
Multimedia Tools and Applications
Efficient broadcast encryption with user profiles
Information Sciences: an International Journal
Proceedings of the 8th international interactive conference on Interactive TV&Video
Exploring synergies between digital tv recommender systems and electronic health records
Proceedings of the 8th international interactive conference on Interactive TV&Video
GameSense: game-like in-image advertising
Multimedia Tools and Applications
Virtual spotlighted advertising for tennis videos
Journal of Visual Communication and Image Representation
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
MediaCRM: enabling customer relationship management in the broadcast
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part I
Property-based collaborative filtering for health-aware recommender systems
Expert Systems with Applications: An International Journal
An ontology-based personalized target advertisement system on interactive TV
Multimedia Tools and Applications
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The traditional broadcasting services such as terrestrial, satellite and cable broadcasting have been unidirectional mass media regardless of TV viewer's preferences. Recently rich media streaming has become possible via the broadband networks. Furthermore, since bidirectional communication is possible, personalcasting such as personalized streaming service has been emerging by taking into account the user's preference on content genres, viewing times and actors/actresses etc. Accordingly personal media becomes an important means for content provision service in addition to the traditional broadcasting service as mass media. In this paper, we introduce a user profile reasoning method for TV viewers. The user profile reasoning is made in terms of genre preference and TV viewing times for TV viewer's groups in different genders and ages. For user profiling reasoning, the TV viewing history data is used to train the proposed user profiling reasoning algorithm which allows for target advertisement for different age/gender groups. To show the effectiveness of our proposed user profile reasoning method, we present plenty of the experimental results by using real TV usage history.