Research on Knowledge Graph Recommendation Method for Online Education
Jin Yang, Chao Duan, Zhaozhuan Zeng, Yumeng Liu, Jingjing Bai, Mingyan Zhang · 2024
With the rapid development of online education, the number of educational resources has increased exponentially. In the face of massive educational resources, learners generally face the problems of information overload and resource trek, and cannot adapt to the rapid growth of educational resources through traditional classification catalogs and search. To solve these problems, providing personalized support services for online education participants has become an urgent idea. In recent years, with the rapid development of knowledge graph technology, a large number of structured knowledge and semantic information are widely used in online education to provide technical support for learners. This paper systematically reviews the current research status of recommendation system, the development trend of knowledge graph technology and the existing research results of recommendation system based on knowledge graph. This paper systematically analyzes the application status of knowledge graph embedding technology in different recommendation scenes, especially summarizes the education-oriented knowledge graph recommendation method in four aspects of learning path, online course, exercise and paper, and points out the advantages and deficiencies of the current research. Finally, the paper looks forward to the development trend of the combination of recommendation technology and knowledge graph in online education, and emphasizes that dynamic recommendation, interpretability and evaluation criteria are important challenges and development directions of personalized service in the future.