Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants

Masahiro Kojima, Masaki Murata, Jun'ichi Kazama, Kow Kuroda, Atsushi Fujita, Eiji Aramaki, Masaaki Tsuchida, Yasuhiko Watanabe, Kentaro Torisawa. Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants. In Ryo Otoguro, Kiyoshi Ishikawa, Hiroshi Umemoto, Kei Yoshimoto, Yasunari Harada, editors, Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation, PACLIC 24, Tohoku University, Japan, 4-7 November 2010. pages 653-660, Institute for Digital Enhancement of Cognitive Development, Waseda University, 2010. [doi]

Abstract

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