TY - GEN
T1 - An eye-tracking study
T2 - 24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016
AU - CHEN, Li
AU - Wang, Feng
N1 - Publisher Copyright:
© 2016 ACM.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/7/13
Y1 - 2016/7/13
N2 - 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.
AB - 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.
KW - Critiquing
KW - Eye tracking
KW - Feedback elicitation
KW - Recommender systems
KW - User study
UR - http://www.scopus.com/inward/record.url?scp=84984870580&partnerID=8YFLogxK
U2 - 10.1145/2930238.2930286
DO - 10.1145/2930238.2930286
M3 - Conference contribution
AN - SCOPUS:84984870580
T3 - UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
SP - 163
EP - 167
BT - UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
PB - Association for Computing Machinery, Inc
Y2 - 13 July 2016 through 17 July 2016
ER -