MATEC Web Conf.
Volume 100, 201713th Global Congress on Manufacturing and Management (GCMM 2016)
|Number of page(s)||6|
|Section||Part 2: Internet +, Big data and Flexible manufacturing|
|Published online||08 March 2017|
Laos Organization Name Using Cascaded Model Based on SVM and CRF
1 School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
2 The Key Laboratory of Intelligent Information Processing, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
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％.
Key words: organization name recognition / conditional random fields (CRF) / support vector machine (SVM) / cascaded model / laos
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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