Abstract In an intelligent education system, accurately updating and constructing course content helps to improve the intelligence of the system and the learning efficiency of students, so this paper constructs an intelligent education system using knowledge graph. The system accomplishes ontology construction, extraction, storage and intelligent question and answer of knowledge through knowledge graph technology to realize the integration of course content. The BI-LSTM-CRF model was used for entity naming of the system’s Q&A function, the Q&A was categorized on the basis of feature extraction, and finally the design of the intelligent educational system was carried out. In the two datasets selected in this paper, the knowledge graph-based learning content recommendation model has the highest F1 value of 98.67% and 97.43%, respectively, and the Q&A system designed in this paper got 75.6% correct among the selected 120 Q&As. It shows that the intelligent education system designed in this paper realizes good interaction effect and course content recommendation update effect.
Lujie Fan (Wed,) studied this question.