Research on Intelligent Question Answering System Based on Medical Knowledge Graph

Qianjun Shuai, Mingjie Wei, Fang Miao, Libiao Jin
{"title":"Research on Intelligent Question Answering System Based on Medical Knowledge Graph","authors":"Qianjun Shuai, Mingjie Wei, Fang Miao, Libiao Jin","doi":"10.1109/IAEAC47372.2019.8997728","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC47372.2019.8997728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

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.
基于医学知识图的智能问答系统研究
随着人工智能的发展,智能医疗系统发挥着越来越重要的作用。传统的医学问答系统只能回答预设的问题。介绍了一种基于知识图谱的智能问答系统模型。分析了如何利用neo4j图形数据库构建知识图谱,并利用卷积神经网络对用户问题进行语义解析。在一定程度上,系统提高了对用户问题的理解,可以给出更好的答案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信