TV Content Recommender System

Srinivas Gutta, Kaushal Kurapati, KP Lee, Jacquelyn Martino, John Milanski, J. David Schaffer, and John Zimmerman, Philips Research

The plethora of content available to the consumer has become overwhelming. Increasing amounts of information are being disseminated through terrestrial broadcast, satellite, and cable leading to an information overload. Common modes of searching for TV programs currently in existence include: TV-guide, PreVue channel and rudimentary search tools available through satellite dish TV programming service. These tools are general-purpose in nature and are not specifically tailored to the individual viewer’s taste. Towards that end we demonstrate a prototype recommender system that searches for TV programs based on their likes/dislikes through implicit personalization techniques.


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