节点文献

基于依存关系的问句理解与问句分类

Question Interpretation and Question Classification Based on Dependency Relations

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 林旭东彭宏林丕源邓健爽

【Author】 LIN Xu-Dong1,2 PENG Hong1 LIN Pi-Yuan2 DENG Jian-Shuang1 ( College of Computer Science & Engineering, South China University of Technology, Guangzhou 510640 (College of Information,South China Agricultural University,Guangzhou 5106422

【机构】 华南理工大学计算机科学与工程学院华南农业大学信息学院华南理工大学计算机科学与工程学院 广州510640广州510642广州510640

【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。

【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.

【基金】 广东省科技攻关项目(A10202001);广州市科技攻关项目(2004Z2-D0091)
  • 【文献出处】 计算机科学 ,Computer Science , 编辑部邮箱 ,2007年07期
  • 【分类号】TP391.1
  • 【被引频次】8
  • 【下载频次】428
节点文献中: 

本文链接的文献网络图示:

本文的引文网络