Review of Movie Recommender Systems Based on Deep Learning

School of Information Technology and Engineering, Guangzhou College of Commerce, Guangzhou, Guangdong 511363, China

^* Corresponding author: 1025312744@qq.com

Abstract

With the development of the network, society has moved into the data era, and the amount of data is exploding, we need a tool to help users find corresponding data collections based on their interests, and recommender systems were born for this purpose. In the movie field, recommender systems suggest items that users may like, improving the efficiency of finding movies and optimizing the user experience thus driving the growth of the movie industry. Machine learning is a multi-disciplinary science that focuses on how to improve the performance of algorithms by continuously reorganizing existing knowledge structures in a way that mimics human learning. Deep learning is a research direction in the field of machine learning that has achieved results in many areas that far surpass previous related techniques. In order to better provide personalized services to users and improve the accuracy of the system’s recommendations, it is necessary to integrate deep learning techniques into the recommender system to optimize the system’s performance. In this paper, we review different approaches in deep learning based recommender systems.