Acquiring unobtrusive relevance feedback through eye-tracking in ambient recommender systems

Abstract:

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. © 2005 The authors. All rights reserved.

Año de publicación:

2005

Keywords:

• Eye-tracking
• Ambient recommender systems
• User modelling
• Implicit relevance feedback

Fuente:

scopus