Research and Implementation of Intelligent Academic Question and Answer System Based on Knowledge Graph

The development of the education system has put forward a high demand for academic Q&A. In this paper, we use technologies such as Flask, WeChat public platform, knowledge graph, and Q&A pair matching to build a knowledge graph containing 9 categories with 20 knowledge entities and more than 200 categories with about 1000 entity attributes in size, using the important notification documents issued by colleges and schools as data sources, and realize an end-to-end intelligent academic Q&A system. The system has the advantages and features of real-time talkability, low latency, high fault tolerance, and human-computer dialogue through natural language. The system has a high value in the Q&A scenario in the field of academic teaching and learning in universities.