Design And Implementation Of Shopping System Based On Personalized Recommendation

With the continuous development of Internet technology and the popularity of network information,people increasingly prefer to buy goods from the online shopping platform.Online shopping platform has brought a lot of convenience to people's lives,it has changed people's shopping habits.Enterprises and individuals can promote and sell products through online shopping platform to increase sales.Information technology continues to update,the site updates and the introduction of a large of goods,attracting a large influx of users.E-commerce system is faced with many challenges,such as the user in the shopping platform will browse the commodity is not interested in and the system can not give users a good shopping guide,it will reduce user experience.And a large number of users will bring great pressure to the system server,it will cause the system to respond to the user's rate of decline and easy to cause the loss of users.This paper focuses on the realization of a high performance,timely response to user requests and personalized recommendation function of online shopping system.The shopping system uses Spring,MyBatis,SpringMVC framework to achieve a portal system and management system personalized recommendation online shopping website.Using collaborative filtering algorithm,custom commodity filter and user label fusion of three ways to achieve personalized recommendation.The online shopping website is divided into back-end commodities and orders maintenance module,consumer oriented portal module,user login module,commodity search module,order module,data service module and personalized recommendation module.The data service module is mainly to provide the service call interface to the front portal.In the system,the SpringMVC annotation is used to develop rest services.Each module in the system is deployed in different containers,which can realize the decoupling of the portal and the server.The system uses Redis for data caching and stores the frequently accessed commodity data into the cache.It can reduce the pressure to access data from the MySql database directly.Using solr to establish commodity data index,the user through the http request call solr services to achieve products search,not accessing the MySql database directly.The system implements the basic functions of online shopping platform,and can be personalized recommendation according to different user preferences.