잠재요인 모델 기반 영화 추천 시스템
- Resource Type
- Article
- Authors
- Chen Ma; 김강철(Kang-Chul Kim)
- Source
- 한국전자통신학회 논문지 16. 1 (2021): 125-133.
- Subject
- Movie Recommendation System
Improved Latent Factor Model
Average Rating
User Bias
Movie Bias
Prediction Rating Range
영화 추천시스템
향상된 잠재요인모델
평균 평점
소비자 편향
영화 편향
예측 평점 구간
- Language
- Korean
- ISSN
- 19758170
With the rapid development of the film industry, the number of films is significantly increasing and movie recommendation system can help user to predict the preferences of users based on their past behavior or feedback. This paper proposes a movie recommendation system based on the latent factor model with the adjustment of mean and bias in rating. Singular value decomposition is used to decompose the rating matrix and stochastic gradient descent is used to optimize the parameters for least-square loss function. And root mean square error is used to evaluate the performance of the proposed system. We implement the proposed system with Surprise package. The simulation results shows that root mean square error is 0.671 and the proposed system has good performance compared to other papers.