Presentation | 2001/3/16 Evaluation of Generality for Multi-language of Word Segmentation Method Using Inductive Learning Wang Zhongjian, Kenji Araki, Koji Tochinai, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We have proposed a method that segments a text into words by using inductive learning, and confirmed the performance to Japanese and Chinese word segmentation by experiments respectively. The method uses only the surface information of characters, so that it is independent on any specific language and a general method. In this paper, we do experiments of Japanese text and Chinese text with same algorithm simultaneously to demonstrate the generality of the method. The results of experiment show that the method is possible to be used to word segmentation of general non-segmented language. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | multi-language / word segmentation / inductive learning / generality |
Paper # | TL2000-44,NLC2000-79 |
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Committee | NLC |
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Conference Date | 2001/3/16(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Evaluation of Generality for Multi-language of Word Segmentation Method Using Inductive Learning |
Sub Title (in English) | |
Keyword(1) | multi-language |
Keyword(2) | word segmentation |
Keyword(3) | inductive learning |
Keyword(4) | generality |
1st Author's Name | Wang Zhongjian |
1st Author's Affiliation | Graduate School of Engineering, Hokkaido University() |
2nd Author's Name | Kenji Araki |
2nd Author's Affiliation | Graduate School of Engineering, Hokkaido University |
3rd Author's Name | Koji Tochinai |
3rd Author's Affiliation | Graduate School of Engineering, Hokkaido University |
Date | 2001/3/16 |
Paper # | TL2000-44,NLC2000-79 |
Volume (vol) | vol.100 |
Number (no) | 700 |
Page | pp.pp.- |
#Pages | 8 |
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