Research On Movie Recommendation Based On Deep Learning Model

The growth rate of information is getting faster and faster.The recommendation system can help people quickly and accurately find the information they are interested in.Therefore,the recommendation system algorithm Research has very important practical significance.In recent years,deep learning technology based on neural networks has made major breakthroughs.Similarly,in the research field of recommendation systems,people have begun to use deep learning to conduct research extensively,and have obtained a lot of research results.Compared with traditional recommendation system algorithms,deep learning algorithms can achieve better results and have a wider range of applicable scenarios.This paper first reviews some improvement researches in the field of recommendation systems in recent years and the research results of the application of deep learning in the personalized recommendation of movies.A more in-depth analysis was carried out to explore the principles of different deep learning models.This paper also uses Movielens,a classic data set,to conduct a research on the personalized recommendation of movies based on deep learning algorithms.It uses two recommendation models based on deep learning,CDAE and Deep FM,and discusses how to use different deep learning models.Model the movie data rated by the user to recommend movies that the user is interested in.Finally,based on the application effect of the actual deep learning model,this paper compares the actual performance of different models with the classic collaborative filtering recommendation system algorithm,analyzes and summarizes the applicability and deficiencies of different models in movie recommendation applications,and gives recommendations suggestions on the application of the system in the film field.