Abstract
This work analyzes the decision-making process underlying choice behavior. First, neural and gaze activity were recorded experimentally from different subjects performing a choice task in a Web Interface. Second, choice models were fitted using rational, emotional and attentional features. The model’s predictions were evaluated in terms of their accuracy and rankings were made for each user. The results show that (1) the attentional models are the best in terms of its average performance across all users, but (2) each subject shows a different best model.
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Acknowledgments
We want to acknowledge the collaboration of Movistar, the leading Spanish Telco, which provided the list of real movies that were used as stimuli during the choice experiments.
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Almomani, A., Monreal, C., Sieira, J., Graña, J., Sánchez, E. (2019). Rational, Emotional, and Attentional Choice Models for Recommender Systems. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 931. Springer, Cham. https://doi.org/10.1007/978-3-030-16184-2_53
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DOI: https://doi.org/10.1007/978-3-030-16184-2_53
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