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基于句法结构分析的中文问题分类
引用本文:文勖,张宇,刘挺,马金山.基于句法结构分析的中文问题分类[J].中文信息学报,2006,20(2):35-41.
作者姓名:文勖  张宇  刘挺  马金山
作者单位:哈尔滨工业大学信息检索研究室
摘    要:问题分类是问答系统中重要的组成部分,问题分类结果的好坏直接影响问答系统的质量。本文提出了一种用于问题分类的特征提取的新方法,该方法主要使用句法分析的结果,提取问题的主干和疑问词及其附属成分作为分类的特征,此方法大幅度地减少了噪音,突出了问题分类的主要特征,利用贝叶斯分类器分类,有效地提高了问题分类的精度。实验结果证明了该方法的有效性,大类和小类的分类精度分别达到了86.62%和71.92%,取得了较好的效果。

关 键 词:计算机应用  中文信息处理  问答系统  问题分类  特征提取  句法分析  
文章编号:1003-0077(2006)02-0033-07
收稿时间:2005-03-12
修稿时间:2006-06-22

Syntactic Structure Parsing Based Chinese Question Classification
WEN Xu,ZHANG Yu,LIU Ting,MA Jin-shan.Syntactic Structure Parsing Based Chinese Question Classification[J].Journal of Chinese Information Processing,2006,20(2):35-41.
Authors:WEN Xu  ZHANG Yu  LIU Ting  MA Jin-shan
Affiliation:Information Retrieval Laboratory , Haerbin Institute of Technology
Abstract:Question classification is very important for question answering,and the result of question classification directly affects the quality of question answering.This paper presents a new method on feature extraction for question classification.The output of syntactic parsing is used in this method to extract the Subject-Predicate structure as well as interrogative words and their adjunctive parts as features for classification,leading to substantial reduction in noise,and emphasis on the main features of question classification.A bayesian classifier is used in classification,which effectively increases the precision of question classification.The experimental result validates the effectiveness of this method: the classification precision of coarse classes and fine classes reach 86.62% and 71.92% respectively,which attains the expected effects.
Keywords:computer application  Chinese information processing  question answering system  question classification  feature extraction  syntactic parsing
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