Research on Intelligent Question Answering System Based on Medical Knowledge Graph
- Resource Type
- Conference
- Authors
- Shuai, Qianjun; Wei, Mingjie; Miao, Fang; Jin, Libiao
- Source
- 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2019 IEEE 4th. :240-243 Dec, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Databases
Diseases
Knowledge discovery
Drugs
Natural languages
Convolutional neural networks
Machine learning
Q/A system
convolutional neural network
knowledge graph
- Language
With the development of artificial intelligence, smart medical systems play an increasingly important role. The traditional medical question answering system can only answer the preset questions. This paper introduces a model of intelligent question answering system based on knowledge graph. It analyzes how to construct a knowledge graph using the neo4j graph database, and uses convolutional neural network to semantically parse user questions. To a certain extent, the system has improved the understanding of user questions and can give better answers.