Preliminary Studies on Personalized Preference Prediction from Gaze in Comparing Visualizations.

This paper presents a pilot study on the recognition of user preference, manifested as the choice between items, using eye movements. Recently, there have been empirical studies demonstrating user task decoding from eye movements. Such studies promote eye movement signal as a courier of user cognitive state rather than a simple interaction utility, supporting the use of eye movements in demanding cognitive tasks as an implicit cue, obtained unobtrusively. Even though eye movements have been already employed in human-computer interaction (HCI) for a variety of tasks, to the best of our knowledge, they have not been evaluated for personalized preference recognition during visualization comparison. To summarize the contribution, we investigate: “How well do eye movements disclose the user’s preference?” To this end, we build a pilot experiment enforcing high-level cognitive load for the users and record their eye movements and preference choices, asserted explicitly. We then employ Gaussian processes along with other classifiers in order to predict the users’ choices from the eye movements. Our study supports further investigation of the observer preference prediction from eye movements.