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
- Anthology ID:
- Y10-1075
- Volume:
- Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation
- Month:
- November
- Year:
- 2010
- Address:
- Tohoku University, Sendai, Japan
- Editors:
- Ryo Otoguro, Kiyoshi Ishikawa, Hiroshi Umemoto, Kei Yoshimoto, Yasunari Harada
- Venue:
- PACLIC
- SIG:
- Publisher:
- Institute of Digital Enhancement of Cognitive Processing, Waseda University
- Note:
- Pages:
- 653–660
- Language:
- URL:
- https://aclanthology.org/Y10-1075
- DOI:
- Cite (ACL):
- Masahiro Kojima, Masaki Murata, Jun’ichi Kazama, Kow Kuroda, Atsushi Fujita, Eiji Aramaki, Masaaki Tsuchida, Yasuhiko Watanabe, and Kentaro Torisawa. 2010. Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants. In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation, pages 653–660, Tohoku University, Sendai, Japan. Institute of Digital Enhancement of Cognitive Processing, Waseda University.
- Cite (Informal):
- Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants (Kojima et al., PACLIC 2010)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/Y10-1075.pdf