摘要
为提高学习者在线学习的效率,本文通过构建课程结构模型,改进已有的协同过滤推荐算法,为在线学习平台设计和实现了一个推荐系统。实践表明,该推荐系统不仅符合学习者的兴趣,还考虑了学习者现有的知识体系,符合学习进程。
In order to improve the efficiency of online learning for learners,this article constructs a course structure model,improves existing collaborative filtering recommendation algorithms,and designs and implements a recommendation system for online learning platforms.Practice has shown that the new recommendation system not only caters to the interests of learners,but also takes into account their existing knowledge system,which is in line with the learning process.
作者
毛雷
MAO Lei(School of Information and Mechanical and Electrical Engineering,Hunan International Economics University,Changsha,China,410006)
出处
《福建电脑》
2024年第6期95-98,共4页
Journal of Fujian Computer
基金
湖南涉外经济学院2023年教学改革研究项目资助。
关键词
在线学习
协同过滤推荐算法
推荐系统
Online Learning
Collaborative Filtering Recommendation Algorithm
Recommendation System