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Detecting preferences based on eye movement using combinatorial fusion

Schweikert, Christina and Shimojo, Shinsuke and Hsu, D. Frank (2016) Detecting preferences based on eye movement using combinatorial fusion. In: IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing. IEEE , Piscataway, NJ, pp. 336-343. ISBN 978-1-5090-3846-6.

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When tasked with comparing two images on a screen, a subject's eye movement can be captured and analyzed in order to understand the process of preference formation. The process of comparing two images and developing a preference is analyzed based on a sample dataset. Although it is known in general that our preferences are shaped by our past experiences, a systemic understanding of the factors which lead to preference decision making remains a challenging problem. In this paper, we propose a set of five attributes which are extracted from the temporal eye movement sequence: last duration, total duration, gaze count, interest sustainability, and region change. Each of these five attributes is a scoring system (ranking system). We then use the combinatorial fusion algorithm (CFA) framework to combine pairs of attributes using the rank-score characteristic (RSC) function and cognitive diversity (CD). Our results demonstrate that combination of two attributes can improve individual attributes if the attribute pair has a higher cognitive diversity. Our work represents a new paradigm to use combinatorial fusion for preference detection based on eye movement.

Item Type:Book Section
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Additional Information:© 2016 IEEE.
Subject Keywords:cognitive diversity, combinatorial fusion algorithm, gaze cascade effect, multiple scoring systems, preference detection
Record Number:CaltechAUTHORS:20170302-084226870
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Official Citation:C. Schweikert, S. Shimojo and D. F. Hsu, "Detecting preferences based on eye movement using combinatorial fusion," 2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), Palo Alto, CA, USA, 2016, pp. 336-343. doi: 10.1109/ICCI-CC.2016.7862057 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:74664
Deposited By: Tony Diaz
Deposited On:02 Mar 2017 19:08
Last Modified:11 Nov 2021 05:28

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