Chat-EasyEdu: An Education Field Intelligent Question-Answering System Based on Knowledge Graphs

In the era of big data, existing knowledge in the field of education is becoming increasingly complex. Proper storage of knowledge in education, improving the singularity of knowledge forms, better retrieval of knowledge, and providing relevant services have become the main issues. To alleviate these problems, this paper constructs an education knowledge graph (KG), providing a set of KG construction paradigms for the education field. Data is collected from publicly available information on the websites of 100 universities and stored in the Neo4j graph database. An intelligent question-answering (IQA) system named Chat-EasyEdu is implemented using matching algorithms. A total of 3720 nodes and 12258 relationships are constructed, and the IQA system is queried and verified using 29 types of questions. The results show that the IQA system can effectively serve users who need to query information about universities, having certain scalability and promotion value.