计算机与现代化

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面向水利信息资源的智能问答系统构建与应用

  

  1. (河海大学计算机与信息学院,江苏南京211100)
  • 收稿日期:2019-07-04 出版日期:2020-03-24 发布日期:2020-03-30
  • 作者简介:张紫璇(1996-),女,江苏徐州人,硕士研究生,研究方向:知识表示学习,智能问答,E-mail: 1064083223@qq.com; 陆佳民(1983-),男,江苏南通人,讲师,CCF专业会员,博士,研究方向:移动对象数据管理,分布式数据处理,水利信息化,E-mail: jiamin.luu@hhu.edu.cn; 姜笑(1994-),女,江苏徐州人,硕士研究生,研究方向:智能问答,知识表示学习; 冯钧(1969-),女,江苏武进人,教授,博士生导师,CCF专业会员,博士,研究方向:时空间数据管理,智能数据处理,数据挖掘,水利信息化。
  • 基金资助:
    国家重点研发计划“水资源高效开发利用”重点专项(2018YFC0407901,2017YFC0405806); 国家自然科学青年基金项目(61602151); 江苏高校文化创意协同创新中心资助项目(XYN1702)

Construction and Application of Intelligent Question Answering System#br# for Water Conservancy Information Resources

  1. (College of Computer and Information, Hohai University, Nanjing 211100, China)
  • Received:2019-07-04 Online:2020-03-24 Published:2020-03-30

摘要: 当前特定领域的问答系统主要采用基于关键字匹配的方法完成问答,类似水库大坝的建成时间、坝高等,无法充分理解用户自然语言提问的检索意图并给出准确回答。为此基于知识图谱技术,利用语义解析方法,本文设计并开发面向水利信息资源的智能问答系统。针对语义解析自然语言问句转化为结构化查询语句需要多步操作,容易导致语义鸿沟问题,还为了后续基于知识表示的问答方法,积累用户语料,本文提出一种语料扩展方法构建语料库。

关键词: 知识图谱, 智能问答, 语义解析, 表示学习

Abstract: Currently, the question-answering system in specific fields mainly adopts the method based on keyword matching to complete the question-answering, which is similar to the construction time and height of the reservoir dam, and cannot fully understand the retrieval intention of users natural language questions and give accurate answers. Therefore, this paper designs and develops an intelligent question answering system for water conservancy information resources based on knowledge mapping technology and semantic analysis. Aiming at the problem of semantic gap caused by the multi-step operation of transforming the natural language questions into structured query statements. This paper also proposes a corpus expansion method to build corpus in order to accumulate user corpus for the subsequent questions and answers based on knowledge representation.

Key words: knowledge graph, intelligent question and answer, semantic analysis, representation learning

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