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基于实例和错误驱动的规则学习方法及其应用
引用本文:王蕾,朱巧明,李培峰,杨季文.基于实例和错误驱动的规则学习方法及其应用[J].计算机应用与软件,2008,25(1):162-164.
作者姓名:王蕾  朱巧明  李培峰  杨季文
作者单位:1. 江苏省计算机信息处理技术重点实验室,江苏,苏州,215006
2. 苏州大学计算机科学与技术学院,江苏,苏州,215006
摘    要:提出了一种基于实例和错误驱动相结合的规则学习方法.该方法首先将提取的文本中的语法结构信息作为实例,然后采用基于转换的错误驱动学习方法找出这些实例的适用上下文环境,从而建立相应的规则库.此方法提取出的规则完全采用机器学习的方式,避免了人工提取规则的主观性缺点.可用于诸如词性标注、未登录词识别、命名实体抽取等自然语言研究课题.

关 键 词:规则学习  中文信息处理  专有名词识别
收稿时间:2006-03-15
修稿时间:2006年3月15日

A RULE LEARNING METHOD BASED ON THE INSTANCE AND ERROR-DRIVING AND ITS APPLICATION
Wang Lei,Zhu Qiaoming,Li Peifeng,Yang Jiwen.A RULE LEARNING METHOD BASED ON THE INSTANCE AND ERROR-DRIVING AND ITS APPLICATION[J].Computer Applications and Software,2008,25(1):162-164.
Authors:Wang Lei  Zhu Qiaoming  Li Peifeng  Yang Jiwen
Affiliation:Wang Lei Zhu Qiaoming Li Peifeng Yang Jiwen (School of Computer Science , Technology,Soochow University,Suzhou 215006,Jiangsu,China)(Key Lab of Computer Information Processing Technology of Jiangsu Province,China)
Abstract:A new rule learning method based on the instance and error-driving is proposed. Grammar structure information is extracted and taken as the instance,and then the context of the instance is found according to the error-driving learning method. Thus,a rule-base is constructed. The model of machine learning is adopted ,and the subjectivity default caused by manual work is avoided. The method could be used in many natural language research subjects, such as unknown word recognition ,part of speech tagging and name entity extraction ,etc.
Keywords:Rule learning Chinese information processing Proper noun recognition
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