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基于知识图谱的智能问答研究综述
引用本文:王智悦,于清,王楠,王耀国.基于知识图谱的智能问答研究综述[J].计算机工程与应用,2020,56(23):1-11.
作者姓名:王智悦  于清  王楠  王耀国
作者单位:1.新疆大学 信息科学与工程学院,乌鲁木齐 830046 2.新疆自治区人民医院 信息中心,乌鲁木齐 830001
基金项目:国家自然科学基金;创新训练项目
摘    要:基于知识图谱的问答是近年来研究热点,从基于模板、语义解析、深度学习、知识图谱嵌入四方面介绍基于知识图谱智能问答实现,归纳了各类方法的优缺点,及尚未解决的关键问题。结合当前人工智能技术发展,重点介绍了基于深度学习的智能问答,有助于更多研究者投身于智能问答研究,根据不同行业需求研发适用于不同领域的问答系统,提高社会智能化信息服务水平。

关 键 词:智能问答  知识图谱  语义解析  深度学习  

Survey of Intelligent Question Answering Research Based on Knowledge Graph
WANG Zhiyue,YU Qing,WANG Nan,WANG Yaoguo.Survey of Intelligent Question Answering Research Based on Knowledge Graph[J].Computer Engineering and Applications,2020,56(23):1-11.
Authors:WANG Zhiyue  YU Qing  WANG Nan  WANG Yaoguo
Affiliation:1.Academy of Information Science and Engineering, Xinjiang University, Urumqi 830046, China 2.Information Center, People’s Hospital of Xinjiang Autonomous Region, Urumqi 830001, China
Abstract:The answer selection model based on knowledge graph has become one of the hottest directions at present. This paper introduces the implementation of answer selection model based on knowledge graph from four aspects of template method, semantic parsing, deep learning and knowledge graph embedding, sums up their advantages, disadvantages and unsolved problem. Combined with the development of artificial intelligence technology, this paper introduces intelligent question-answer system based on deep learning. This research is helpful for more researchers to devote themselves to the intelligent question-answer system and develops different kinds of intelligent question-answer system to improve the social intelligent information service.
Keywords:intelligent questions and answers  knowledge graph  semantic analysis  deep learning  
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