Abstract
Emotions have an impact to almost all decisions. They affect our choices and are activated as feedback during the decision process. This work aims at investigating whether behavior patterns can be learned and used to predict the user’s choice. Specifically, we focused on pairwise image comparisons in a preference elicitation experiment, and exploited a Process Mining approach to learn preferences. We proposed and evaluated a strategy based on experienced emotions and gaze behaviour, whose results show promising prediction performance.
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Notes
- 1.
Head pose estimation using OpenCV and Dlib: https://www.learnopencv.com/.
- 2.
Sequential, parallel, conditional, or iterative composition.
- 3.
Given a workflow and an intermediate status of a process execution, the goal is predicting how the execution might proceed, or what kind of process is being enacted, among a set of candidates.
- 4.
Users will be ignored since the interest is not on user’s profiling.
- 5.
- 6.
The range between the first and third quartile.
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Angelastro, S., De Carolis, B.N., Ferilli, S. (2019). Predicting User Preference in Pairwise Comparisons Based on Emotions and Gaze. In: Wotawa, F., Friedrich, G., Pill, I., Koitz-Hristov, R., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2019. Lecture Notes in Computer Science(), vol 11606. Springer, Cham. https://doi.org/10.1007/978-3-030-22999-3_23
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