Design and Implementation of Movie Recommender System Based on Graph Database

with the continuous development of Internet technology, information overload is becoming more and more serious. It's getting harder to get useful information from the network. Although the search engine can help users find information they need from the vast amounts of information in a certain extent, but cannot completely solve the problem of information overload, when users cannot accurately describe the information they need, you need to recommend system to help users find valuable information for users. So recommender systems are becoming more and more important. The movie recommender system implemented in this paper is based on the traditional user-based collaborative filtering algorithm, and the user project scoring matrix is pre filled. At the same time, database technology of this system uses graph database which is good at dealing with complex relations. In data visualization, the degree of recommendation of a movie is expressed by the size of the node and the thickness of the edge, so as to improve the user experience.