Personalized emotional prediction method for real-life objects based on collaborative filtering

Authors:
Hyeong-Joon Kwon;Hyeong-Oh Kwon;Kwang-Seok Hong
Affiliations:
School of Information and Communication Enginnering, Sungkyunkwan University, Kyungki-do, South Korea;School of Information and Communication Enginnering, Sungkyunkwan University, Kyungki-do, South Korea;School of Information and Communication Enginnering, Sungkyunkwan University, Kyungki-do, South Korea
Venue:
EPCE'11 Proceedings of the 9th international conference on Engineering psychology and cognitive ergonomics
Year:
2011

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Abstract

In this paper, we propose a personalized emotional prediction method using the user's explicit emotion. The proposed method predicts the user's emotion based on Thayer's 2-dimensional emotion model, which consists of arousal and valence. We construct a user-object dataset using a self-assessment manikin about IAPS photographs, and predict the target user's arousal and valence by collaborative filtering. To evaluate performance of the proposed method, we divide the user-object dataset into a test set and training set, and then observe the difference between real emotion and predicted emotion in the 2-dimensional emotion model. As a result, we confirm that the proposed method is effective for predicting the user's emotion.