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This paper demonstrates Interest Beat (InBeat.eu) as a recommender system for online videos, which determines user interest in the content based on gaze tracking with Microsoft Kinect in addition to explicit user feedback. Content of the videos is represented using a semantic wikifier. User profile is constructed from preference rules, which are discovered with an association rule learner.
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