We examine two basic sources for implicit relevance feedback on the segment level for search personalization: eye tracking and display time. A controlled study has been conducted ...
Understanding how people interact with search engines is important in improving search quality. Web search engines typically analyze queries and clicked results, but these actions...
In this paper we predict the relevance of images based on a lowdimensional feature space found using several users’ eye movements. Each user is given an image-based search task,...
Zakria Hussain, Kitsuchart Pasupa, John Shawe-Tayl...
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 s...
We examine the effect of incorporating gaze-based attention feedback from the user on personalizing the search process. Employing eye tracking data, we keep track of document part...