Design And Implementation Of The Music Recommendation System Based On User Behavior

The rapid development of Internet and mobile informatization has led to more and more information received by people on mobile terminals and networks.Undoubtedly,the Internet has become the largest information distribution center in human history.But it is also a double-edged sword.In the face of a lot of complicated information,it is increasingly difficult for users to get the content they are interested in.The traditional search engine can solve part of the information overload problem,but due to the high repeatability of the search keywords,it is still difficult for ordinary search to filter out the information that the user wants.The recommendation system came into being for solving the problem called information overload.The advent of the era of pan-entertainment Internet has made the recommendation system widely used in music,movies,information and other apps.Foreign Pandora,Last.fm radio,Youtube,domestic Douban FM,Netease cloud music,etc.,all rely on their excellent recommendation algorithm to obtain a large number of loyal users.Improvements in network infrastructure have made it possible for users to discover,download,and listen to music anytime,anywhere,but the proportion of users actively searching for and discovering music has continued to decline in recent years.Accurate personalized recommendations not only help users solve music acquisition and filtering problems,but also help music content providers get more traffic and increase revenue.Collecting user behavior and completing music recommendations based on user behavior is the focus of this music recommendation system.The system collects user listening,collection and other behaviors,converts these behaviors into user's interest in songs,and then adopts item-based collaborative filtering and user-based collaborative filtering technology to complete personalized music list recommendation.The system uses JAVA programming language to complete background server development,and completes system design and implementation based on B / S architecture and WEB open sourceframework SSM architecture.The full text is based on software development process,through requirements analysis,system design,system implementation and system testing,and finally a music recommendation system that can meet the user's song listening needs and personalized recommendations based on user behavior.