poster

Tell Me What You See, I Will Tell You What You Remember

Authors:

Florian Marchal,

Sylvain Castagnos,

Anne BoyerAuthors Info & Claims

UMAP '16: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization

Pages 293 - 294

https://doi.org/10.1145/2930238.2930265

Published: 13 July 2016 Publication History

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Abstract

Recommender systems usually rely on users' preferences. Nevertheless, there are many situations (e-learning, e-health) where recommendations should rather be based on their memory. So as to infer in real time and with low involvement what has been memorized by users, we propose in this paper to establish a link between gaze features and visual memory. We designed a user experiment where 24 subjects had to remember 72 images. In the meantime, we collected 18,643 fixation points. Among other metrics, our results show a strong correlation between the relative path angles and the memorized items.

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Cited By

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Lyu CChen HPeng XYe JWang H(2023)Optical Character Recognition (OCR)-Based and Gaussian Mixture Modeling-OCR-Based Slide-Level “With-Me-Ness”: Automated Measurement and Feedback of Learners’ Attention State during Video LecturesInternational Journal of Human–Computer Interaction10.1080/10447318.2023.220427240:15(3952-3971)Online publication date: 7-May-2023
https://doi.org/10.1080/10447318.2023.2204272
Eraslan SYesilada YHarper S(2020)“The Best of Both Worlds!”ACM Transactions on the Web10.1145/337249714:1(1-31)Online publication date: 9-Jan-2020
https://dl.acm.org/doi/10.1145/3372497

Index Terms

Tell Me What You See, I Will Tell You What You Remember
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User models
2. Information systems
  1. Data management systems
  2. World Wide Web
    1. Web searching and information discovery
      1. Personalization

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Information & Contributors

Information

Published In

UMAP '16: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization

July 2016

366 pages

ISBN:9781450343688

DOI:10.1145/2930238

General Chairs:
Julita Vassileva
University of Saskatchewan, Canada
,
James Blustein
Dalhousie University, Canada
,
Program Chairs:
Lora Aroyo
VU Amsterdam, the Netherlands
,
Sidney D'Mello
University of Notre Dame, USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 July 2016

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UMAP '16

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UMAP '16: User Modeling, Adaptation and Personalization Conference

July 13 - 17, 2016

Nova Scotia, Halifax, Canada

Acceptance Rates

UMAP '16 Paper Acceptance Rate 21 of 123 submissions, 17%;

Overall Acceptance Rate 162 of 633 submissions, 26%

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UMAP '25

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33rd ACM Conference on User Modeling, Adaptation and Personalization

June 16 - 19, 2025

New York City , NY , USA

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Cited By

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Lyu CChen HPeng XYe JWang H(2023)Optical Character Recognition (OCR)-Based and Gaussian Mixture Modeling-OCR-Based Slide-Level “With-Me-Ness”: Automated Measurement and Feedback of Learners’ Attention State during Video LecturesInternational Journal of Human–Computer Interaction10.1080/10447318.2023.220427240:15(3952-3971)Online publication date: 7-May-2023
https://doi.org/10.1080/10447318.2023.2204272
Eraslan SYesilada YHarper S(2020)“The Best of Both Worlds!”ACM Transactions on the Web10.1145/337249714:1(1-31)Online publication date: 9-Jan-2020
https://dl.acm.org/doi/10.1145/3372497

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Recommendations

Tell Me What You Want: Embedding Narratives for Movie Recommendations

What Can History Tell Us?

Research Overview of Educational Recommender Systems