Integrating Information Sources for Recommender Systems

SILVANA ACIAR; JOSEFINA LÓPEZ HERRERA; JOSEP LLUIS DE LA ROSA I ESTEVA

Frontiers in Artificial Intelligence and Applications AI Research & Development

IOS Press

Lugar: Amsterdam, The Netherlands; Año: 2005; p. 405 - 412

The acquisition of relevant information to maintain up-to-date user’s preferences is crucial in recommender systems in order to close the cycle of recommendations. Ambient Intelligence is a suitable approach to close the loop in nonintrusive way in recommender systems using ambient eye trackers. We combine a method to acquire relevance feedback through eye-tracking with 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 behaviors.