Adaptive user interface of product recommendation based on eye-tracking
Shiwei Cheng, Xiaojian Liu, Pengyi Yan, Jianbo Zhou, Shouqian Sun · 2010
To reduce the intrusive interaction and workload for the product recommendations, we seek implicit methods to indicate users' preferences and recommend desirable products on the interface automatically. In this paper, we validate our approach with interactive genetic algorithm to compute fitness based on the eye-movement data metrics. And construct the adaptation strategies for content and layout design on the user interface. A digital camera recommendation prototype is proposed, and in the user study, we find that users can get interested products information with less physical effort and more satisfactions.