Design And Implementation Of Personalized Music Recommendation System

With the development of the Internet and big data technology,big data technology is used to process massive data,dig information resources,and create more value.Nowadays,various large websites are full of all kinds of information,from shopping to travel,from food delivery to news information and audio information.We need to use big data technology to mine data through massive data.In this background,The personalized recommendation systems are particularly broad.For the vast amount of music resource information on the Internet,people need a recommendation system to achieve accurate and fast recommendation.We need to use intelligent recommendation algorithms to analyze the preferences of users,and use big data technology to process the massive audio resources.The user recommends the song that best suits the user's preferences to achieve accurate positioning of audio resource information.The personalized music recommendation system is to analyze different datas generated by the operating system,and then personalize the user,thereby proactively recommending information software systems that can meet their interests and needs.The personalized music recommendation system is based on the B / S model and uses the SSM framework to build the website system.The overall business logic is built through Spring and deployed on Tomcat.This article mainly implements the system's music recommendation function,music search,music score,music collection function,and user information and music management.The personalized recommendation function is implemented according to the steps of data collection,data preprocessing,data analysis,user dynamic interest modeling,recommendation candidate set screening,and recommendation result display.The clustering algorithm and the decomposition machine factor are mainly used to establish the user interest model,and the collaborative filtering algorithm is used to obtain the recommendation results.The music search part realizes query with the singer according to the music name;with the help of music scoring and music collection operations,information about user behavior data is obtained,whichmakes the establishment of user interest models more accurate.The design and implementation of the personalized music recommendation system can greatly improve the accurate analysis and positioning of users by Music Network,improve the user experience and the overall optimization design of the music system,and achieve good results.