首页 | 官方网站   微博 | 高级检索  
     

基于依存关系的问句理解与问句分类
引用本文:林旭东,彭宏,林丕源,邓健爽.基于依存关系的问句理解与问句分类[J].计算机科学,2007,34(7):208-210.
作者姓名:林旭东  彭宏  林丕源  邓健爽
作者单位:1. 华南理工大学计算机科学与工程学院,广州510640;华南农业大学信息学院,广州510642
2. 华南理工大学计算机科学与工程学院,广州510640
3. 华南农业大学信息学院,广州510642
基金项目:广东省科技攻关计划 , 广东省广州市科技攻关项目
摘    要:问句理解是问答系统的首要过程,问句分类是问句理解的主要组成部分,它在问答系统中具有非常重要的作用,因为问句类型有助于在文档中定位和抽取答案。问句分类的目标是基于预期的答案类型,准确地分类问句。本文提出依存关系规则与统计方法相结合,实现了基于依存关系的中文问句理解与问句分类机制。实验表明:支持向量机结合依存关系的特征抽取方法,获得了较高问句分类正确率。

关 键 词:问句分类  依存关系  依存关系树  命名实体识别

Question Interpretation and Question Classification Based on Dependency Relations
LIN Xu-Dong,PENG Hong,LIN Pi-Yuan,DENG Jian-Shuang.Question Interpretation and Question Classification Based on Dependency Relations[J].Computer Science,2007,34(7):208-210.
Authors:LIN Xu-Dong  PENG Hong  LIN Pi-Yuan  DENG Jian-Shuang
Abstract:Question interpretation is the first step of question answering system. Question classification is the main part of the question interpretation and it plays a crucial important role in the question answering system because categorizing a given question is beneficial to identify an answer in the documents. The goal of question classification is to accurately assign labels to question based on expected answer type. In this paper, we use dependency relation rules and statistical method to understand questions and classify questions. In this experiment, we perform the SVM algorithm and a dependency relationships feature extraction method to get high classification accuracy.
Keywords:Question classification  Dependency relations  Dependency tree  Named entity recognition
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《计算机科学》浏览原始摘要信息
点击此处可从《计算机科学》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号