Research on Personalized Recommendation Technology for Learning Resources Combining Knowledge Graph and Interest Diffusion Mechanism

Abstract

Under the background of Internet technology maturing gradually, the acquisition of learning resources has become increasingly convenient. However, the accompanying “Information Explosion” makes it easy for learners to get lost in the ocean of learning materials and also make it difficult to find the resources they really need. In the face of this reality, it is urgent to explore the implementation and optimization of personalized recommendation technology. In order to make the personalized recommendation technology play a greater role in the field of education, this paper studies a learning resource recommendation algorithm which combines knowledge graph and interest diffusion mechanism, and makes a structure analysis of the recommendation system. Because the proposed technology considers the domain features of the recommended object, it reflects the combination of technology and education, and is of certain reference significance for further research on personalized recommendation of learning resources and personalized learning.