自动应答系统中自然语言理解技术的研究  

Research on the Technology of Natural Language Understanding in Question Answer System

作　　者：郭庆琳[1] 樊孝忠[1] 

机构地区：[1]北京理工大学计算机系,北京100081

出　　处：《计算机应用研究》2004年第6期24-25,43,共3页Application Research of Computers

基　　金：国家重点基础研究发展规划"973"资助项目(G1 9980 30 71 1 )

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。Automatic 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 dissertated 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 were exercised,it proved that they are feasible and effective.

关 键 词：自动应答系统 语义网络 LSF模型 谓词逻辑 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]