Design of Open Source Personalized Information Recommendation System for Web Pages in Big Data Environment

The current web information recommendation system can not meet the personalized needs of users. To solve this problem, an open source personalized information recommendation system for web pages is proposed in the large data environment. The hardware of the system is PC-side web pages, and its development environment consists of the underlying database, software environment, development technology and user interface. Based on the hardware design of the system, the software is designed and the corresponding functions are realized, so that the software can run steadily on the platform. By collecting user data, user feature collaborative filtering, personalized correlation matching, recommendation ranking weighting and recommendation evaluation criteria, the software is designed and implemented by code. The experimental results show that the system can recommend suitable personalized information for users, and the system has advantages and reliability.