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›› 2004, Vol. 30 ›› Issue (13): 15-.

• 论文 • 上一篇    下一篇

基于自然语言理解的自动应答系统

郭庆琳,樊孝忠   

  1. 北京理工大学计算机系,北京理工大学计算机系 北京 100081 华北电力大学计算机系,北京 102206
  • 发布日期:2004-07-15

Question Answer System Based on Natural Language Understanding

GUO Qinglin1,2, FAN Xiaozhong1   

  1. (1.Department of Computer Science, Beijing Institute of Technology, Beijing 100081; 2. Department of Computer Science, Huabei Electric Power University, Beijing 102206)
  • Published:2004-07-15

摘要: 自动应答系统(QAS )是一种基于因特网的高性能软件系统。它的核心技术是基于自然语言理解的相关技术,包括知识库和语料库的建设、文本的切分和标注、句子的语法分析和语义分析等。重点论述了自动应答系统中知识信息的语义网络表示和LSF随机化句法分析模型,以及自动应答系统的结构与组成,并对LSF模型进行了参数训练,实践证明这些技术是可行的。通过开发银行的“受限领域自动应答系统”项目,这些技术被证明是高效的、可推广的。

关键词: 自动应答系统, 语义网络, LSF模型, 谓词逻辑

Abstract: Question answer system(QAS )is a kind of high-powered software system based on Internet. Its key technology is the interrelated technology based on natural language understanding, including the construction of knowledge base and corpus, the word segmentation and POS tagging of text, the grammatical analysis and semantic analysis of sentences etc. This thesis dissertates mainly the denotation of knowledge-information based on semantic network in QAS, the stochastic syntax-parse model named LSF of knowledge-information in QAS, the structure and constitution of QAS. And the LSF model's parameters are exercised, it proves that they are feasible. At the same time, through "the limited-domain QAS" which is exploited for banks, these technologies are proved effective and propagable.

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