基于知识图谱的用户兴趣挖掘与在线课程推荐系统  

User Interest Mining and Online Course Recommendation System Based on Knowledge Graph

作　　者：周颖 ZHOU Ying(Guangxi Electrical Polytechnic Institute,Nanning 530299,China)

机构地区：[1]广西电力职业技术学院,广西南宁530299

出　　处：《智能物联技术》2024年第1期54-57,共4页Technology of Io T& AI

基　　金：广西高校中青年教师科研基础能力提升项目(2023KY1365)。

摘　　要：随着互联网技术的发展,在线教育平台的课程资源急剧增加,如何为用户推荐合适的课程成为一项重要的研究方向。为此,研究一种基于知识图谱的用户兴趣挖掘与在线课程推荐方法。首先,设计在线课程推荐系统的总体框架。其次,聚焦知识图谱构建,进行兴趣挖掘和推荐的方法。最后,采用MOOCCube数据集进行实验验证。结果表明,所提方法可以满足课程推荐的需求。With the development of Internet technology,the course resources of online education platform increase sharply.How to recommend suitable courses for users has become an important research direction.Therefore,this paper studies a method of user interest mining and online course recommendation based on knowledge graph.Firstly,the overall framework of online course recommendation system is designed.Secondly,focus on knowledge graph construction,interest mining and recommendation methods.Finally,the MOOCCube dataset was used for experimental verification.The results show that the proposed method can meet the requirement of course recommendation.

关 键 词：在线课程 推荐系统 知识图谱 兴趣挖掘 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]