@inproceedings{c6c23288618547d28fcbf641cb5dee45,
title = "An eye-tracking study: Implication to implicit critiquing feedback elicitation in recommender systems",
abstract = "The critiquing-based recommender system (CBRS) stimulates users to critique the recommended item in terms of its attribute values. It has been shown that such critiquing feedback can effectively improve users' decision quality, especially in complex decision environments such as e-commerce, tourism, and finance. However, because its explicit elicitation process unavoidably demands extra user efforts, the application in real situations is limited. In this paper, we report an eye-tracking experiment with the objective of studying the relationship between users' eye gazes as laid on recommended items and their critiquing feedback. The results indicate the feasibility of inferring users' feedback based on their eye movements. It hence points out a promising roadmap to developing unobtrusive eye-based feedback elicitation for recommender systems.",
keywords = "Critiquing, Eye tracking, Feedback elicitation, Recommender systems, User study",
author = "Li CHEN and Feng Wang",
note = "Publisher Copyright: {\textcopyright} 2016 ACM. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016 ; Conference date: 13-07-2016 Through 17-07-2016",
year = "2016",
month = jul,
day = "13",
doi = "10.1145/2930238.2930286",
language = "English",
series = "UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization",
publisher = "Association for Computing Machinery (ACM)",
pages = "163--167",
booktitle = "UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization",
address = "United States",
}