Abstract
We investigate and propose a knowledge graph-based method and implementation of the question-and-answer (Q&A) system for COVID-19 cases imported from abroad. It mainly analyzes and organizes the knowledge graph construction methods based on knowledge acquisition and visualization. In addition, this paper implements the knowledge graph-based Q&A system by training term frequency-inverse document frequency (TF-IDF) model and Bidirectional Long Short-Term Memory + Conditional Random Field (Bi-LSTM+CRF) model as well as Cypher query statements using the graph database Neo4j. Finally, the visual intelligent interface of the Q&A system is designed to meet user requirements and realize the function of accurate Q&A.