基于协同过滤的新闻推荐系统：Flask 框架开发

随着网络的快速发展，利用网络来进行管理系统也逐渐开始发展，网上管理模式很快融入到了人们的眼球之中，随之就产生了'基于协同过滤的新闻推荐系统'，这样就让基于协同过滤的新闻推荐系统信息管理更加方便简单。 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。通过测试达到较好效果，利用先进的计算机技术和网络技术来改变目前的基于协同过滤的新闻推荐系统管理状况，提高管理效率。

With the rapid development of the internet, the use of online management systems has gradually begun to develop, and online management models have quickly become integrated into people's consciousness, resulting in the emergence of 'news recommendation systems based on collaborative filtering', which makes information management of news recommendation systems more convenient and simple. This system was developed by analyzing the current situation of news recommendation systems both domestically and abroad, 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: 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. The development of the system included system analysis, administrator use case diagrams, user use case diagrams, database table design, detailed design, and code implementation. The system achieved good results through testing, using advanced computer and network technologies to change the current management situation of news recommendation systems based on collaborative filtering, and improve management efficiency.