A movie rating prediction system of user propensity analysis based on collaborative filtering and fuzzy system

Authors:
Taeryong Jeon;Jaewoo Cho;Soojin Lee;Gyeongdong Baek;Sungshin Kim
Affiliations:
School of Electrical Engineering, Pusan National University, Busan, Korea;School of Electrical Engineering, Pusan National University, Busan, Korea;School of Electrical Engineering, Pusan National University, Busan, Korea;School of Electrical Engineering, Pusan National University, Busan, Korea;School of Electrical Engineering, Pusan National University, Busan, Korea
Venue:
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Year:
2009

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Abstract

Recently, an intelligent system is developed for proper service which isn't passive system. Recent system can answer and recommend to user before user's request. This intelligent system is used for personalized recommendation system and representative techniques are content-based and collaborative filtering. In this study, we propose a prediction system which is based on the techniques of recommendation system using a collaborative filtering and fuzzy system to solve the collaborative filtering problems. In order to verify the prediction system, we used the user's rating data about movies. We predicted the user's rating using this data. The accuracy of this prediction system is determined by computing the predicted RMSE (Root mean square error) of the system against the actual rating about the each movie. And predicted RMSE is compared with the existing system. Thus, this prediction system can be applied to base technology of recommendation system and also recommendation of multimedia such as music and books.