Collaborative Filtering-Based News Recommendation System: Development and Implementation

With the rapid development of the internet, using it for management systems has gradually begun to develop. Online management modes quickly caught people's attention, leading to the emergence of 'news recommendation systems based on collaborative filtering'. This makes information management for news recommendation systems based on collaborative filtering more convenient and simple.

This system was developed by analyzing the current situation of news recommendation systems, the key technologies and implementation methods of collaborative filtering algorithms, and the feasibility of the project. The project was developed based on the Flask framework, with Python as the programming language and MySQL as the backend database. The system is mainly used by two types of users: users and administrators. The main functions include user management, news management, and comment management for administrators, and 'My Comments' and 'Recommended News' for users.

The system analysis, administrator use case diagram, user use case diagram, database table design, detailed design, and code implementation were completed during the system development. Through testing, the system achieved good results, using advanced computer and network technology to improve the management efficiency of news recommendation systems based on collaborative filtering.