Learning Resource Recommendation Model of Treatise on Febrile Diseases Course Based on Knowledge Graph
Combined with the knowledge graph and personalized resource recommendation algorithm,the personalized recommendation of the course learning resources of Treatise on Febrile Diseases is realized to help learners learn more effectively.The knowledge graph in the early research is used to integrate the knowledge of the course ontology to construct the course knowledge graph of Treatise on Febrile Diseases.On this basis,combined with collaborative filtering and path-based recommendation algorithms,a hybrid recommendation algorithm is designed to recommend learning resources to users according to similarity ranking.It provides formal knowledge representation methods and organizational models to meet personalized learning needs,provides learners with resources that are in line with their learning paths,and achieves accurate push.This model can effectively solve the problems of"obscure and difficult to read,boring and difficult to focus,and difficult to interact in teaching"in the course teaching of Treatise on Febrile Diseases,which is helpful for learners to better learn the course of Treatise on Febrile Diseases.
course knowledge graphTreatise on Febrile Diseasesresource recommendation algorithmpersonalized learning
国家科技期刊平台
NSTL
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