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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/9545

タイトル: A Semi-Supervised Learning Method for Vietnamese Part of Speech Tagging
著者: Nguyen, Le Minh
Xuan, Bach Ngo
Nguyen, Viet Cuong
Nhat, Minh Pham Quang
Shimazu, Akira
キーワード: Semi-Supervised Learning
Part of Speech Tagging
Natural Language Processing
発行日: 2010-10
出版者: Institute of Electrical and Electronics Engineers (IEEE)
誌名: 2010 Second International Conference on Knowledge and Systems Engineering (KSE)
開始ページ: 141
終了ページ: 146
DOI: 10.1109/KSE.2010.35
抄録: This paper presents a semi-supervised learning method for Vietnamese part of speech tagging. We take into account two powerful tagging models including Conditional Random Fields (CRFs)and the Guided Online-Learning models (GLs) as base learning models. We then propose a semi-supervised learning tagging model for both CRFs and GLs methods. The main idea is to use of a word-cluster model as an associate source for enrich the feature space of discriminate learning models for both training and decoding processes. Experimental results on Vietnamese Tree-bank data (VTB) showed that the proposed method is effective. Our best model achieved accuracy of 94.10% when tested on VTB, and 92.60% an independent test.
Rights: Copyright (C) 2010 IEEE. Reprinted from 2010 Second International Conference on Knowledge and Systems Engineering (KSE), 2010, 141-146. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
URI: http://hdl.handle.net/10119/9545
資料タイプ: publisher
出現コレクション:b11-1. 会議発表論文・発表資料 (Conference Papers)


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