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

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.