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Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants
Masahiro Kojima
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Masaki Murata
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Jun’ichi Kazama
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Kow Kuroda
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Atsushi Fujita
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Eiji Aramaki
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Masaaki Tsuchida
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Yasuhiko Watanabe
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Kentaro Torisawa
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Paper Details:
Month: November
Year: 2010
Location: Tohoku University, Sendai, Japan
Venue:
PACLIC |
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No Citations Yet
http://202.218.239.69/aramaki/TRANS/
http://cl.aist-nara.ac.jp/taku-
Field Of Study
Task
Tagging
Information Retrieval
Language
Chinese
English
Japanese
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