Presentation 2001/3/16
Evaluation of Generality for Multi-language of Word Segmentation Method Using Inductive Learning
Zhongjian Wang, Kenji Araki, Koji Tochinai,
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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.
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Keyword(in English) multi-language / word segmentation / inductive learning / generality
Paper # TL2000-44,NLC2000-79
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Committee TL
Conference Date 2001/3/16(1days)
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Registration To Thought and Language (TL)
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 Zhongjian Wang
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) 698
Page pp.pp.-
#Pages 8
Date of Issue