Personalized Recommendation of Learning Resources Based on Knowledge Graph

Abstract

Personalized learning resources recommendation is one of the crucial problems under the background of internet plus education. The current personalized learning resources recommendation methods are mostly based on the learner's basic information and learning behavior, without considering the logical relation between the learning resources. With above consideration, we use knowledge graph to construct the class model. And then we propose an efficient personalized recommendation algorithm based on the interest similarity and knowledge connection degree and design a related recommendation system. Taking the discrete mathematics as an instance, we verify the correctness and effectiveness of our recommendation algorithm by experiment.