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CCIA
2005
Springer

Acquiring Unobtrusive Relevance Feedback through Eye-Tracking in Ambient Recommender Systems

10 years 7 months ago
Acquiring Unobtrusive Relevance Feedback through Eye-Tracking in Ambient Recommender Systems
Acquiring relevant information to keep user’s preferences up-to-date is crucial in recommender systems in order to close the cycle of recommendations. Ambient Intelligence is a suitable approach for non-intrusively closing the loop in recommender systems using ambient eye-trackers. We combine a method for acquiring relevance feedback through eye-tracking with the functionalities of an extractor agent. We describe the results of experiments conducted in a recommender system to obtain implicit feedback using eye fixations. Finally, we obtain a ranking of user’s most relevant preferences and behaviours. Keywords. User Modelling, Ambient Recommender Systems, Implicit Relevance Feedback, Eye-Tracking
Gustavo González, Beatriz López, Cec
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where CCIA
Authors Gustavo González, Beatriz López, Cecilio Angulo, Josep Lluís de la Rosa
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