基于用户协同过滤算法的E-Learning平台个性化推荐研究  

Research on Personalized Recommendation of E-Learning Platform Based on User Collaborative Filtering

作　　者：耿晓利[1] 邓添文 罗桦锋 许佳惠 Geng Xiao-li;DENG Tian-wen;LUO Hua-feng;XU Jia-hui(Department of Network Technology, Huasoftware College, Guangzhou University, Guangzhou 510990)

机构地区：[1]广州大学华软软件学院网络技术系

出　　处：《现代计算机》2019年第17期30-33,共4页Modern Computer

基　　金：2017年广东省重点平台及科研项目(No.2017GXJK257);2018年大学生创新创业训练计划项目(No.201812618036)

摘　　要：在线学习(E-Learning)是一种深受欢迎的学习方式,但由于其资源众多,用户选择学习资源时无从下手,消耗掉较多的寻找时间。因此,根据用户的需要向其精准推荐课程是十分有必要的。通过挖掘E-Learning平台的用户数据特点,实现基于用户协同过滤的个性化课程推荐,实验结果显示,可以较好地帮助用户快速发现有价值的学习资源,减少选择资源的时间,有利于提高用户的学习效率,也可帮助用户快速良好地建立自身的知识体系。E-learning is a popular learning method, but because of its much of resources, users can't get started when they choose to learn resources, and they consume more time to find. Therefore, it is very necessary to accurately recommend courses according to the needs of users. By mining the characteristics of user data of E-learning platform, implements the personalized course recommendation based on user collaborative filtering. The experimental results show that it can help users quickly find valuable learning resources and reduce the time for selecting resources, improve user learning efficiency, and help users quickly and well establish their own knowledge system.

关 键 词：E-LEARNING 协同过滤 个性化推荐 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]