Inproceedings,
TV personalization system - Design of a TV show recommender engine and interface
PERSONALIZED DIGITAL TELEVISION: TARGETING PROGRAMS TO INDIVIDUAL VIEWERS, page 27-51. PO BOX 17, 3300 AA DORDRECHT, NETHERLANDS, SPRINGER, (2004)3rd Conference on User Modeling, Johnstown, PA, JUN 23, 2003.
Abstract
The arrival of PVRs (Personal Video Recorders)-tape less devices that
allow for easy navigation and storage of TV content-and the
availability of hundreds of TV channels in US homes have made the task
of finding something good to watch increasingly difficult. In order to
ease this content selection overload problem, we pursued three related
research themes. First, we developed a recommender engine that tracks
users' TV-preferences and delivers accurate content recommendations.
Second, we designed a user interface that allows easy navigation of
selections and easily affords inputs required by the recommender
engine. Third, we explored the importance of gaining users' trust in
the recommender by automatically generating explanations for content
recommendations. In evaluation with users, our smart interface came out
on top beating TiVo's interface and TV Guide Magazine, in terms of
usability, fun, and quick access to TV shows of interest. Further, our
approach of combining multiple recommender ratings-resulting from
various machine-learning methods-using neural networks has produced
very accurate content recommendations.
