Using Quantitative Context Relevance Analysis for Text Segmentation

作     者：Maosheng ZHONG~(1,2) Hui LIU~1 Lei LIU~1 ~1Department of Compute Science and Engineering,Shanghai Jiaotong University,ShangHai 200240,China ~2 School of Information Engineering,East China Jiaotong University,NanChang,330013,China 

会议名称：《第四届全国信息检索与内容安全学术会议》

会议日期：2008年

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Major Research Program of NSFC(Grant No.60496326:Basic Theory and Core Techniques of Non Canonical) the Science & Technology Project of JiangXi Provincial Department of Education(Grant No.178) 

关 键 词：Text segmentation Quantified conceptual relations Context relevance measure Gap point Segmentation value 

摘      要：Text segmentation technique can divide a text into topic-coherent *** segmenting,some Natural Language Processing tasks,such as Text Classification,Text Summarization,Information Retrieval or Q-A program etc.,will be more easier to ***,two key problems of text segmentation are how to identify whether there exists relevance or not in the context of a text and how to apply the result of context relevance analysis to detect topic-breaks between different *** this paper,we presented a practical method to measure the relevance of context based on Quantified Conceptual Relations of word-pairs,extracted from Modem Chinese Standard *** built a scoring model,which can calculate the score of gap point between sentences by using the quantitative relevance of context,to implement the sentence-level text *** experimental results show that Mean Error Rate ■ and Minimum Error Rate P of our method for identifying the segment boundaries are the lowest in the state-of-the-art methods for Chinese text segmentation.