[1]吴家皋,周凡坤,张雪英.HMM模型和句法分析相结合的事件属性信息抽取[J].南京师大学报(自然科学版),2014,37(01):30.
　WuJiagao,Zhou Fankun,Zhang Xueying.Research of the Extraction Method of Event Properties Based on the Combining of HMM and Syntactic Analysis[J].Journal of Nanjing Normal University(Natural Science Edition),2014,37(01):30.
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HMM模型和句法分析相结合的事件属性信息抽取()
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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第37卷
期数:
2014年01期
页码:
30
栏目:
计算机科学
出版日期:
2014-03-30

文章信息/Info

Title:
Research of the Extraction Method of Event Properties Based on the Combining of HMM and Syntactic Analysis
作者:
吴家皋1; 2; 周凡坤1; 2; 张雪英3
(1.南京邮电大学计算机学院,江苏 南京 210003) (2.江苏省无线传感网高技术研究重点实验室,江苏 南京 210003) (3.南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023)
Author(s):
Wu1Jiagao1; 2; Zhou Fankun1; 2; Zhang Xueying3
(1.School of Computer Science & Technology,Nanjing University of Posts and Telecommunications,Nanjing 210003,China) (2.Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks,Nanjing 210003 China) (3.MOE Key Laboratory of Virtual Geographic Environment,Nanjing Normal University,Nanjing 210023,China)
关键词:
自然语言处理; 中文文本信息抽取; 隐马尔科夫模型; 句法分析; 触发词
Keywords:
natural language processing; information extraction of Chinese text; hidden markov model; syntactic analysis; trigger words
分类号:
TP181
文献标志码:
A
摘要:
自然语言处理技术是计算机科学领域与人工智能领域中的一个重要方向,其中信息抽取是近年来新兴起的一个研究领域.由于汉语自身结构松散、语法语义灵活等特点,使得中文文本中信息抽取具有较大的难度.本文提出句法分析和隐马尔科夫模型相结合的事件属性抽取方法,其主要思想是先利用句法分析对中文文本进行分析,将得到的句法结构交给隐马尔科夫模型进行学习得到一个抽取模型,然后再由此模型对中文文本进行抽取.实验表明,该方法具有较高的准确率和召回率.
Abstract:
Natural language processing technology is an important direction in the field of computer science and artificial intelligence,and the Chinese text information extraction is a new rising researching field in recent years.Due to the character of the loose structure of Chinese text,the flexibility of grammar and semanteme,the research of Chinese natural language processing has a difficult challenge nowadays.In the paper,a method of the combine of syntactic and HMM(Hidden Markov Model)was proposed.The main idea is to use syntax to analyze the Chinese text,then submit the syntactic structure to HMM and get a HMM model through learning it,finally the event properties can be extracted by the HMM model.The experiment shows that the method has higher precision and recall than normal algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2013-08-10.
基金项目:国家863项目(2012AA12A403)、江苏省自然科学基金(BK2012833)、江苏省高校自然科学基金(12KJB520011).
通讯联系人:吴家皋,博士,副教授,研究方向:计算机网络、移动计算、GIS应用等.E-mail:jgwu@njupt.edu.cn
更新日期/Last Update: 2014-03-30