计算机应用与软件2012，Vol.29Issue(3)：108-111,4.
中文问句分类特征的研究
STUDY ON CLASSIFICATION FEATURES OF CHINESE INTERROGATIVES
摘要
Abstract
Different classification features of interrogatives differ in their impacts on interrogative classification, and the time complexities of the extraction and treatment of these features are dissimilar as well. To address this issue, in this article we propose such a method, it picks up six classification features, including the interrogative word of the question, the main sememe of core keyword (the first and second-level dependent word of the interrogative word and the kernel word of interrogatives ) , the first sememe of core keyword, the main sememe of interrogatives' subject-predicate-accusative words, the named entities and the singular/plural form of nouns, it adopts the classification algorithm of support vector machine to carry out the classification contrast experiments on fact interrogatives with different feature combinations. It is found that the main sememe of core keyword extracted by the word sense disambiguation technology not only impacts the accuracy rate of classification evidently but also greatly reduces the dimensions of eigenvector and the processing time.关键词
问题分类/主要义原/词义消岐/支持向量机Key words
Question classification/Main sememe/Word sense disambiguation/Support vector machine分类
信息技术与安全科学引用本文复制引用
牛彦清,陈俊杰,段利国,张巍..中文问句分类特征的研究[J].计算机应用与软件,2012,29(3):108-111,4.基金项目
国家自然科学基金项目(60970059) （60970059）
山西省国际科技合作计划(2009081022). （2009081022）
