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引入混合特征的最大名词短语双向标注融合算法

李业刚 黄河燕 鉴萍

李业刚, 黄河燕, 鉴萍. 引入混合特征的最大名词短语双向标注融合算法. 自动化学报, 2015, 41(7): 1274-1282. doi: 10.16383/j.aas.2015.c140598
引用本文: 李业刚, 黄河燕, 鉴萍. 引入混合特征的最大名词短语双向标注融合算法. 自动化学报, 2015, 41(7): 1274-1282. doi: 10.16383/j.aas.2015.c140598
LI Ye-Gang, HUANG He-Yan, JIAN Ping. A Combination Algorithm of Bi-directional Labeling in Identifying of Maximal-length Noun Phrases with Hybrid Feature. ACTA AUTOMATICA SINICA, 2015, 41(7): 1274-1282. doi: 10.16383/j.aas.2015.c140598
Citation: LI Ye-Gang, HUANG He-Yan, JIAN Ping. A Combination Algorithm of Bi-directional Labeling in Identifying of Maximal-length Noun Phrases with Hybrid Feature. ACTA AUTOMATICA SINICA, 2015, 41(7): 1274-1282. doi: 10.16383/j.aas.2015.c140598

引入混合特征的最大名词短语双向标注融合算法

doi: 10.16383/j.aas.2015.c140598
基金项目: 

国家重点基础研究发展计划(973计划) (2013CB329303),国家自然科学基金(61132009, 61202244, 61201352)资助

详细信息
    作者简介:

    黄河燕北京理工大学计算机学院教授.1989年获中国科学院计算所博士学位.主要研究方向为语言信息处理,机器翻译. E-mail: hhy63@bit.edu.cn

A Combination Algorithm of Bi-directional Labeling in Identifying of Maximal-length Noun Phrases with Hybrid Feature

Funds: 

Supported by National Basic Research Program of China (973 Program) (2013CB329303), and National Natural Science Foundation of China (61132009, 61202244, 61201352)

  • 摘要: 最大名词短语的识别对机器翻译等诸多自然语言处理任务有着重要的意义. 以汉语最大名词短语识别为研究任务,在分析现有方法的基础上,从汉语的语言学 特殊性以及基于支持向量机的序列标注算法的特点出发,考查了基于混合特征的融合算法的适应性. 实验证明,采用词和基本组块混合标注单元的标注方法对汉语最大名词短语的识别 是有效的,并且其正反向识别结果具有一定的互补性, 在此基础上提出的基于"边界分歧"的双向序列标注融合算法恰能发 掘双向识别的互补性,并达到较高的融合精度.
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出版历程
  • 收稿日期:  2014-09-12
  • 修回日期:  2015-02-16
  • 刊出日期:  2015-07-20

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