An eye-tracking study: Implication to implicit critiquing feedback elicitation in recommender systems

Li CHEN, Feng Wang

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationUMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
PublisherAssociation for Computing Machinery, Inc
Pages163-167
Number of pages5
ISBN (Electronic)9781450343701
DOIs
Publication statusPublished - 13 Jul 2016
Event24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016 - Halifax, Canada
Duration: 13 Jul 201617 Jul 2016

Publication series

NameUMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization

Conference

Conference24th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2016
Country/TerritoryCanada
CityHalifax
Period13/07/1617/07/16

Scopus Subject Areas

  • Software

User-Defined Keywords

  • Critiquing
  • Eye tracking
  • Feedback elicitation
  • Recommender systems
  • User study

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