Publication detail

Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A Preliminary Analysis

DE LEON MARTINEZ, S. MORO, R. BIELIKOVÁ, M.

Original Title

Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A Preliminary Analysis

Type

conference paper

Language

English

Original Abstract

Eye tracking in recommender systems can provide an additional source of implicit feedback, while helping to evaluate other sources of feedback. In this study, we use eye tracking data to inform a collaborative filtering model for movie recommendation providing an improvement over the click-based implementations and additionally analyze the area of interest (AOI) duration as related to the known information of click data and movies seen previously, showing AOI information consistently coincides with these items of interest

Keywords

Eye Tracking, Recommender Systems, Collaborative Filtering, AOI Processing, Movie Recommendation, Implicit Feedback 

Authors

DE LEON MARTINEZ, S.; MORO, R.; BIELIKOVÁ, M.

Released

30. 3. 2023

Publisher

Association for Computing Machinery

Location

New York, NY

ISBN

979-8-4007-0150-4

Book

ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications

Pages from

1

Pages to

3

Pages count

3

URL

https://dl.acm.org/doi/10.1145/3588015.3589511

BibTex

@inproceedings{BUT184811,
  author="DE LEON MARTINEZ, S. and MORO, R. and BIELIKOVÁ, M.",
  title="Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A Preliminary Analysis",
  booktitle="ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications",
  year="2023",
  pages="1--3",
  publisher="Association for Computing Machinery",
  address="New York, NY",
  doi="10.1145/3588015.3589511",
  isbn="979-8-4007-0150-4",
  url="https://dl.acm.org/doi/10.1145/3588015.3589511"
}