计算机应用与软件Issue(4)：51-55,5.DOI:10.3969/j.issn.1000-386x.2014.04.013
基于支持向量机的中文文本蕴涵识别研究
ON SVM-BASED CHINESE TEXTUAL ENTAILMENT RECOGNITION
摘要
Abstract
Textual entailment relation research mainly aims to build a common framework for textual inference and solve the problem of semantic expression diversity in natural language at the same time.In this paper,we come down the recognition of Chinese textual entailment relation to a kind of classification problem,and then construct the classification model based on support vector machine for classifying the semantic relations between the given Chinese text pairs.It mainly adopts the statistic,lexical semantic and syntactic correlated classification features.Experimental results show that the SVM-based multiple classifiers can effectively recognise the Chinese textual entailment relation.关键词
文本蕴涵/支持向量机/统计特征/词汇语义特征/句法特征Key words
Textual entailment/Support vector machine(SVM)/Statistic feature/Lexical semantic feature/Syntactic feature分类
信息技术与安全科学引用本文复制引用
李妍,刘茂福,姬东鸿..基于支持向量机的中文文本蕴涵识别研究[J].计算机应用与软件,2014,(4):51-55,5.基金项目
国家自然科学基金项目（61100133，61173062）；武汉科技大学大学生创新基金项目（11ZRB105）。 （）
