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基于双层模型的维吾尔语突发事件因果关系抽取

钟军 禹龙 田生伟 吐尔根·依布拉音

钟军, 禹龙, 田生伟, 吐尔根·依布拉音. 基于双层模型的维吾尔语突发事件因果关系抽取. 自动化学报, 2014, 40(4): 771-779. doi: 10.3724/SP.J.1004.2013.00771
引用本文: 钟军, 禹龙, 田生伟, 吐尔根·依布拉音. 基于双层模型的维吾尔语突发事件因果关系抽取. 自动化学报, 2014, 40(4): 771-779. doi: 10.3724/SP.J.1004.2013.00771
ZHONG Jun, YU Long, TIAN Sheng-Wei, TurgLm IBRAHIM. Causal Relation Extraction of Uyghur Emergency Events Based on Cascaded Model. ACTA AUTOMATICA SINICA, 2014, 40(4): 771-779. doi: 10.3724/SP.J.1004.2013.00771
Citation: ZHONG Jun, YU Long, TIAN Sheng-Wei, TurgLm IBRAHIM. Causal Relation Extraction of Uyghur Emergency Events Based on Cascaded Model. ACTA AUTOMATICA SINICA, 2014, 40(4): 771-779. doi: 10.3724/SP.J.1004.2013.00771

基于双层模型的维吾尔语突发事件因果关系抽取

doi: 10.3724/SP.J.1004.2013.00771
基金项目: 

国家自然科学基金(61262064,60963017,61063026,61063043),国家社会科学基金(10BTQ045,11XTQ007)资助

详细信息
    作者简介:

    钟军 新疆大学硕士研究生.主要研究方向为自然语言处理.E-mail:zjbrilliant@126.com

Causal Relation Extraction of Uyghur Emergency Events Based on Cascaded Model

Funds: 

Supported by National Natural Science Foundation of China (61262064, 60963017, 61063026, 61063043), National Social Science Foundation of China (10BTQ045, 11XTQ007)

  • 摘要: 针对传统事件因果关系识别覆盖范围小和人工标注代价高等不足,提出了一种基于双层模型的维吾尔语突发事件因果关系抽取方法. 该方法采用分治思想,将因果关系抽取问题转化为对事件序列的两次模式识别标注. 采用Bootstrapping算法,在第一次模式识别时,标注因果关系的语义角色,并将标注的语义角色标签作为新的特征传递给第二层模式识别,用于因果关系边界标注. 该方法用于维吾尔语突发事件显式因果关系的抽取准确率为85.39%,召回率为77.53%,证明了本文提出的方法在维吾尔语主题突发事件因果关系抽取上的有效性和实用性.
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出版历程
  • 收稿日期:  2012-12-19
  • 修回日期:  2013-05-02
  • 刊出日期:  2014-04-20

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