Publication Details
Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A Preliminary Analysis
DE LEON MARTINEZ, S.; MORO, R.; BIELIKOVÁ, M. Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A Preliminary Analysis. In ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications. New York, NY: Association for Computing Machinery, 2023. p. 1-3. ISBN: 979-8-4007-0150-4.
Czech title
Sledování očí jako zdroj implicitní zpětné vazby v doporučovacích systémech: Předběžná analýza
Type
conference paper
Language
English
Authors
URL
Keywords
Eye Tracking, Recommender Systems, Collaborative Filtering, AOI Processing, Movie Recommendation, Implicit Feedback
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
Published
2023
Pages
1–3
Proceedings
ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications
ISBN
979-8-4007-0150-4
Publisher
Association for Computing Machinery
Place
New York, NY
DOI
UT WoS
001031497300074
EID Scopus
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"
}