A Learning Path Recommendation Method for Knowledge Graph of Professional Courses

In this era of information explosion, in order to help students select suitable resources when facing a large number of online courses, this paper proposes a knowledge graph-based learning path recommendation method to bring personalized course recommendations to students. The knowledge graph of professional courses is realized by completing the construction of the ontology library of online courses, and the graph database Neo4j is used to store the knowledge graph. SpringBoot is used to build the backend system and implement a set of course recommendation algorithm to filter the learning resources after analyzing the courses students have taken and the quality of course learning, and generate a list of course recommendations for each student. After developing the system based on this method, it can effectively help learners recommend course learning paths and greatly meet students' learning needs.