Design And Implementation Of A Personalized Recommendation System For Online Shopping Platforms

With the increasing popularity of computer networks and the rapid development of e-commerce,in this open network environment,people are not only content to browse and find information on the Internet,but also more and more people are involved in various commercial trade activities.Online shopping has become a part of people’s lives as a fashionable way of shopping.In order to further satisfy the needs of modern people,a personalized recommendation system for online shopping platforms based on the B/S architecture is designed.Through the understanding of user interests and hobbies,the collection of data such as user browsing history records and user collections will be Electronic products with reference value can effectively recommend users,so as to improve user service satisfaction,improve user shopping experience,and help sales companies quickly sell goods.This topic not only analyzes the current situation of personalized recommendation of online shopping platform,but also conducts in-depth research and comparison of the existing online shopping platform personalized recommendation system.Based on this research,a set of JSP-based online shopping platform personalized recommendation system was designed and developed.The front desk of this system mainly uses JSP as the development language of the system.The background uses MySQL as the database management system.The server uses Tomcat 7.0.The development environment uses MyEclipse 10.The Java Web is one of the most popular Web application development technologies.A development tool design online shopping platform personalized recommendation system.The online shopping platform personalized recommendation system implements functions such as user registration,user login,user personal information management,order information management,favorites management,comment management,etc.,and realizes the personalized demand for online shopping of customers.