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基于支持向量机的问句分析
引用本文:刘颖,韩杰,滕至阳.基于支持向量机的问句分析[J].微机发展,2007,17(8):1-4.
作者姓名:刘颖  韩杰  滕至阳
作者单位:东南大学计算机科学与工程学院 江苏南京210096
基金项目:国家“十五”重大科技攻关项目(2509000012)
摘    要:为提高问答系统对问句理解的准确率,以概念层次网络理论结合传统计算语言学为思路,提出了适用于限定领域中问句分析模型,根据限定领域的知识特点,设计了新的问句分类方法。在此问句分类方法的基础上,构建了基于支持向量机理论的问句分类器。在以实际教学过程中所收集的真实问句为问题集和训练集的测试中,取得了较好的实践效果。

关 键 词:概念层次网络理论  问句分类  支持向量机  中文信息处理  问答系统
文章编号:1673-629X(2007)08-0001-04
修稿时间:2006年10月9日

Research of Question Analysis Based on Support Vector Machine
LIU Ying,HAN Jie,TENG Zhi-yang.Research of Question Analysis Based on Support Vector Machine[J].Microcomputer Development,2007,17(8):1-4.
Authors:LIU Ying  HAN Jie  TENG Zhi-yang
Abstract:A novel closed-domain oriented question analysis module based on hierarchical network of concepts and traditional computational linguistics is proposed to enhance the rate of accuracy of question interpretation of a question answering system.A new question catalog is developed on the basis of characteristics of closed-domain.A novel question classifier based on support vector machine is constructed on the grounds of this new catalog.The result of experiments tested on questions gathered during process of instruction shows better promise to this method.
Keywords:hierarchical network of concepts theory  question catalog  support vector machine  Chinese information processing  question answering system
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