| 最大熵模型的事件分类 |
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| 引用本文： | 于江德,李学钰,樊孝忠,庞文博.最大熵模型的事件分类[J].电子科技大学学报(社会科学版),2010(4). |
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| 作者姓名： | 于江德 李学钰 樊孝忠 庞文博 |
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| 作者单位： | 安阳师范学院计算机与信息工程学院;北京理工大学计算机科学技术学院; |
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| 基金项目： | 教育部博士点基金(20050007023) |
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| 摘 要： | 提出了一种基于最大熵模型的事件分类方法,该方法能够综合事件表述语句中的触发词信息及各类上下文特征对事件进行分类。对其中的两个关键问题:参数估计、特征模板与特征选择进行了详细论述,采用IIS算法学习模型参数,使用增量选择方法选择特征。应用该方法对人民日报语料中的职务变动、会见、恐怖袭击、法庭宣判、自然灾害五类事件进行了分类实验,结果表明,该方法的分类效果明显优于传统的分类方法。
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| 关 键 词： | 事件信息抽取 事件分类 事件表述语句 最大熵模型 触发词 |
Event Classification Based on Maximum Entropy Model |
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| YU Jiang-de,LI Xue-yu,FAN Xiao-zhong, PANG Wen-bo.Event Classification Based on Maximum Entropy Model[J].Journal of University of Electronic Science and Technology of China(Social Sciences Edition),2010(4). |
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| Authors: | YU Jiang-de LI Xue-yu FAN Xiao-zhong PANG Wen-bo |
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| Institution: | YU Jiang-de1,LI Xue-yu1,FAN Xiao-zhong2,, PANG Wen-bo2 (1. School of Computer , Information Engineering,Anyang Normal University Anyang Henan 455002,2. School of Computer Science , Technology,Beijing Institute of Technology Haidian Beijing 100081) |
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| Abstract: | An approach based on maximum entropy model is proposed for event classification. This approach can classify the events by merging the features about trigger and context in event mention sentences. The key of the method is parameter estimation and feature selection,which are discussed in detail. IIS algorithm is employed for parameter estimation and incremental method is used for feature selection. Experiments are performed on management succession,meeting,terror attack,judicial adjudicate,and natural disast... |
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| Keywords: | event information extraction event classification event mention sentence maximum entropy model trigger |
| 本文献已被 CNKI 等数据库收录！ |
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