基于事件语义特征的中文文本蕴含识别  

Event Semantic Feature Based Chinese Textual Entailment Recognition

作　　者：刘茂福[1,2] 李妍[1,2] 姬东鸿[3] 

机构地区：[1]武汉科技大学计算机科学与技术学院,湖北武汉430065 [2]智能信息处理与实时工业系统湖北省重点实验室,湖北武汉430065 [3]武汉大学计算机学院,湖北武汉430072

出　　处：《中文信息学报》2013年第5期129-136,共8页Journal of Chinese Information Processing

基　　金：国家自然科学基金资助项目(61100133;61173062);国家社会科学基金重大资助项目(11&Z189);湖北省教育厅人文社科基金重点资助项目(2011jyte126)

摘　　要：为了强化文本蕴含系统深层语义分析与推理能力,该文提出了基于事件语义特征的中文文本蕴含识别方法。该方法基于事件标注语料生成事件图,将文本间的蕴含关系转化为事件图间的蕴含关系;利用最大公共子图的事件图相似度算法计算事件语义特征,与统计特征、词汇语义特征和句法特征一起使用支持向量机进行分类,得到初步实验结果,再经过基于事件语义规则集合的修正处理得到最后的识别结果。实验结果表明基于事件语义特征的中文文本蕴含识别方法可以更有效地对中文文本蕴含关系进行识别。In order to strengthen deep semantic analysis and inference of textual entailment,this paper proposes the method of event semantic feature based Chinese textual entailment recognition.The method generates event graphs base on event labeled corpus,and then the entailment recognition between text pairs can be changed to entailment recognition between event graphs.The event semantic feature can be computed based on max-common sub-graph.The event semantic feature combined with the surface statistical feature,lexical semantic feature and syntactic feature is used to classify textual entailment based on support vector machine and can obtain the preliminary experimental result,and the correction module based on event semantic rules handles preliminary experimental result to get the final experimental result.The experimental results show that the event semantic feature based Chinese textual entailment recognition is effective and efficient in Chinese textual entailment recognition.

关 键 词：文本蕴含 事件语义特征 最大公共子图 支持向量机 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]