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计算机系统应用:2019,28(1):245-250
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基于SVM-BiLSTM-CRF模型的财产纠纷命名实体识别方法
周晓磊1, 赵薛蛟2,1, 刘堂亮3, 宗子潇4, 王其乐5, 里剑桥6
(1.中国科学院 沈阳计算技术研究所, 沈阳 110168;2.中国科学院大学, 北京 100049;3.辽宁省人民检察院沈阳铁路运输分院, 沈阳 110001;4.东北大学, 沈阳 110000;5.沈阳市第三十一中学, 沈阳 110021;6.大连理工大学, 大连 116621)
Named Entity Recognition Method of Judgment Documents with SVM-BiLSTM-CRF
ZHOU Xiao-Lei1, ZHAO Xue-Jiao2,1, LIU Tang-Liang3, ZONG Zi-Xiao4, WANG Qi-Le5, LI Jian-Qiao6
(1.Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China;2.University of Chinese Academy of Sciences, Beijing 100049, China;3.Shenyang Railway Transportation Branch of Liaoning People's Procuratorate, Shenyang 110001, China;4.Northeastern University, Shenyang 110000, China;5.Shenyang Thirty-first Middle School, Shenyang 110021, China;6.Dalian University of Technology, Dalian 116621, China)
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投稿时间:2018-05-24    修订日期:2018-06-15
中文摘要: 裁判文书中的命名实体识别是自动化审判的关键一步,如何能够有效的分辨出案件的关键命名实体是本文的研究重点.因此本文针对财产纠纷审判案件,提出了一种基于SVM-BiLSTM-CRF的神经网络模型.首先利用SVM筛选出包含关键命名实体的句子,然后将正确包含此类实体的句子转化为字符级向量作为输入,构建适合财产纠纷裁判文书命名实体识别的BiLSTM-CRF深层神经网络模型.通过构建训练数据进行验证和对比,该模型比其他相关模型表现出更高的召回率和准确率.
中文关键词: 命名实体识别  SVM  BiLSTM  CRF
Abstract:The recognition of the named entity in the judgment documents is the key step in the automatic trial. How to effectively distinguish the key named entity of the case is the key point in this study. Therefore, this study proposes a neural network model based on SVM-BiLSTM-CRF for property dispute of trial cases. First, the sentences containing the key named entities are selected by SVM, and then the sentences are converted into the character level vectors as input, and the BiLSTM-CRF deep neural network model suitable for the identification of the property dispute referee's named entity is constructed. By constructing training data for verification and comparison, the model shows higher recall and accuracy than other related models.
keywords: named entity  SVM  BiLSTM  CRF
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周晓磊,赵薛蛟,刘堂亮,宗子潇,王其乐,里剑桥.基于SVM-BiLSTM-CRF模型的财产纠纷命名实体识别方法.计算机系统应用,2019,28(1):245-250
ZHOU Xiao-Lei,ZHAO Xue-Jiao,LIU Tang-Liang,ZONG Zi-Xiao,WANG Qi-Le,LI Jian-Qiao.Named Entity Recognition Method of Judgment Documents with SVM-BiLSTM-CRF.COMPUTER SYSTEMS APPLICATIONS,2019,28(1):245-250

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