摘要
文章面向在线教育,研究并设计一种课程学习视频的推荐系统。由于线上学习资源冗杂繁多,且缺乏规范化构建和系统化管理,学习者难以精准获取满足其个性化需求的课程学习视频。文章通过数据挖掘技术获取用户数据后构建用户画像并进行相似用户群体识别,再利用推荐算法实现课程学习视频与用户之间的精准匹配。实验结果表明,该文推荐系统可以有效解决人们在选择学习资源时产生的“信息迷航”和“信息过载”等问题,能够有效满足用户个性化学习需求并为用户提供个性化学习路线。
This paper studies and designs a course learning video recommendation system for online education.As online learning resources are numerous,and lack of standardized construction and systematic management,it's hard for online learners to catch accurately course learning videos that meet their personalized needs.This paper obtains user data through data mining technology,constructs user profiles,identifies similar user groups,and then uses recommendation algorithms to achieve precise matching between course learning videos and users.The experimental results indicate that,the recommendation system proposed in this paper can effectively solve the problems of“information confusion”and“information overload”that people encounter when choosing learning resources,and can effectively meet users'personalized learning needs and provide personalized learning routes for users.
作者
陈玉帛
项慨
王顺驰
何希
李娅琴
邹正
李玉婷
CHEN Yubo;XIANG Kai;WANG Shunchi;HE Xi;LI Yaqin;ZOU Zheng;LI Yuting(Hubei University of Economics,Wuhan 430205,China)
出处
《现代信息科技》
2023年第9期1-8,共8页
Modern Information Technology
基金
大学生创新创业训练计划支持省级创新训练项目(S202211600024)。
关键词
课程学习视频
用户画像
个性化推荐
推荐系统
course learning video
user portrait
personalized recommendation
recommendation system
