文本摘要的建构渗透度特征模型  

Document Summarization Based on Penetrability of Key Words

作　　者：任立园 谢振平[1,2] 刘渊 REN Liyuan;XIE Zhenping;LIU Yuan(School of Digital Media,Jiangnan University,Wuxi,Jiangsu 214122,China;Jiangsu Key Laboratory of Media Design and Software Technology,Wuxi,Jiangsu 214122,China)

机构地区：[1]江南大学数字媒体学院,江苏无锡214122 [2]江苏省媒体设计与软件技术重点实验室,江苏无锡214122

出　　处：《中文信息学报》2018年第7期74-81,共8页Journal of Chinese Information Processing

基　　金：江苏省自然科学基金(BK20130161);国家自然科学基金(61572236);国家科技支撑计划(2015BAH54F01)

摘　　要：旨在实现从海量的文本数据中快速准确地获取关键信息。为探索新颖的摘要句特征因素,该文将文句中的关键词嵌入知识网络进行建模,并将文句映射至知识网络进行表达,进而提出文句的关键词建构渗透度特征模型,在摘要句判别中引入文句中关键词组的宽度和深度的渗透特性。结合最大熵建模分类方法,针对领域语料库进行不同特征的影响系数建模,实现了监督学习下摘要句的有效分类和自动提取。文中实验结果良好,表明了新特征模型的有效性和在领域语料库中的稳定性,且特征计算方法简洁,具有良好的综合实用性。Automatic document summarization aims to extract brief and important information from massive texts.In order to further explore novel features for text summarization,knowledge network is introduced to model document information.Specifically,key words of documents are viewed as network nodes,sentences are represented as the paths of sequential key words on knowledge network.Then,the feature model for the penetrability of key words is proposed,in which width and depth of penetrability of key words are defined to measure each sentence.A maximum entropy based document summarization model is implemented with the proposed feature,which is validated in the experiments for its effectiveness.

关 键 词：文本摘要 文句关键词 知识网络 渗透度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]