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汉语定义语句的抽取方法 被引量：1

Extraction of Chinese Sentences for Definition
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摘要 该文介绍了在汉语文本中抽取定义语句的方法。方法的主要特点是:给定被定义的词汇(字符串),应用Bo-yer-Moore算法查找该串在文本中的位置,继而在该句子中查找符合定义特征的谓词。在这个工作基础上,根据谓词字符串的特征排除谓词歧义,并按照句法分析的结果对定义语句修饰谓词的不同语法单元进行识别,从而实现了基于字符串和语法特征的识别的定义语句抽取。 Using Boyer-Moore algorithm and grammar parsing technology,the paper studies extracting the Chinese sentences,which make some definitions,in texts.In the work,defined words,verbs and some functional phrases for definition are recognized so a more precise extractions are completed,and some words which might make incorrect extractions are avoided.
作者 张寅生
机构地区 中国科学技术信息研究所
出处 《计算机与数字工程》 2011年第10期45-47,112,共4页 Computer & Digital Engineering
关键词 知识抽取 信息抽取 汉语句子识别 定义语句 BOYER-MOORE算法 自然语言理解 knowledge extraction information extraction Chinese sentence recognition definition recognition Boyer-Moore algorithm natural language processing
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献7

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二级参考文献24

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共引文献30

同被引文献9

  • 1]iang Huixing,Wang Xiaojie, Tian Jilei. Second-order HMM for event extraction from short message [ J ]. Lecture Notes in Computer Science,2010,6 177 : 149-156.
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  • 7Souyma Ray, Mark Craven. Representing sentence structure in hidden markov models for information extraction [ C ]// Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence. Washington: Morgan Kanfmann Publishers,2001 : 1 273-1279.
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  • 9梁吉光,田俊华,姜杰.基于改进HMM的文本信息抽取模型[J].计算机工程,2011,37(20):178-179. 被引量：9

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计算机与数字工程
2011年 第10期

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