本系统通过分析新闻推荐系统的国内外现状、协同过滤算法的关键技术及实现方式及项目的可行性后进行开发的课题基于flask框架开发编程语言选择的是python使用MySQL作为后台数据库。系统主要供用户和管理员两类人员使用。主要功能包括：管理员角色的用户管理、新闻管理、评论管理用户角色的我的评论、推荐新闻。系统开发中完成了系统分析、管理员用例图、用户用例图以及数据库表设计、详细设计、代码功能实现。通过测

This system was developed based on the analysis of the current situation of news recommendation systems both domestically and abroad, key technologies and implementation methods of collaborative filtering algorithms, and the feasibility of the project. The project was developed using the Flask framework and Python programming language, with MySQL as the backend database. The system is mainly used by two types of users: administrators and regular users. Its main functions include user management, news management, and comment management for administrators, and "My Comments" and recommended news for regular users. During the development process, the system analysis, use case diagrams for administrators and regular users, database table design, detailed design, and code implementation were completed. The system achieved good results through testing, using advanced computer and network technologies to improve the current management situation of collaborative filtering-based news recommendation systems and enhance management efficiency.