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  • 标题:Laos Organization Name Using Cascaded Model Based on SVM and CRF
  • 本地全文:下载
  • 作者:Shaopeng Duan ; Shaopeng Duan ; Lanjiang Zhou
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2017
  • 卷号:100
  • 页码:1-6
  • DOI:10.1051/matecconf/201710002051
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:According to the characteristics of Laos organization name, this paper proposes a two layer model based on conditional random field (CRF) and support vector machine (SVM) for Laos organization name recognition. A layer of model uses CRF to recognition simple organization name, and the result is used to support the decision of the second level. Based on the driving method, the second layer uses SVM and CRF to recognition the complicated organization name. Finally, the results of the two levels are combined, And by a subsequent treatment to correct results of low confidence recognition. The results show that this approach based on SVM and CRF is efficient in recognizing organization name through open test for real linguistics, and the recalling rate achieve 80. 83%and the precision rate achieves 82. 75%.
  • 关键词:organization name recognition;conditional random fields (CRF);support vector machine (SVM);cascaded model;laos
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