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J-GLOBAL ID:201102292285864667   Reference number:11A1907067

Learning High-performance Dependency Parsing Models by Large-scale Semi-supervised Learning

大規模データを用いた半教師あり学習による高精度係り受け解析モデルの学習
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Volume: 52  Issue: 11  Page: 3038-3051  Publication year: Nov. 15, 2011 
JST Material Number: Z0778B  ISSN: 1882-7837  Document type: Article
Article type: 原著論文  Country of issue: Japan (JPN)  Language: JAPANESE (JA)
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Natural language processing  ,  Artificial intelligence 
Reference (29):
  • 1) Buchholz, S. and Marsi, E.: CoNLL-X Shared Task on Multilingual Dependency Parsing, Proc. CoNLL-X, pp.149-164 (2006).
  • 2) Nivre, J., Hall, J., Kübler, S., McDonald, R., Nilsson, J., Riedel, S. and Yuret, D.: The CoNLL 2007 Shared Task on Dependency Parsing, Proc. EMNLP-CoNLL, pp.915-932 (2007).
  • 3) Yamada, H. and Matsumoto, Y.: Statistical Dependency Analysis with Support Vector Machines, Proc. IWPT (2003).
  • 4) McDonald, R., Crammer, K. and Pereira, F.: Online Large-margin Training of Dependency Parsers, Proc. ACL, pp.91-98 (2005).
  • 5) McDonald, R., Pereira, F., Ribarov, K. and Hajič, J.: Non-projective Dependency Parsing using Spanning Tree Algorithms, Proc. HLT-EMNLP, pp.523-530 (2005).
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