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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 4/2015

01.08.2015 | Original Article

A bilingual word alignment algorithm of Vietnamese-Chinese based on feature constraint

verfasst von: Yuanyuan Mo, Jianyi Guo, Zhengtao Yu, Lin Luo, Shengxiang Gao

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 4/2015

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Abstract

It is difficult to achieve auto-alignment between Vietnamese and Chinese, because their syntax and structure are quite different. In this case we present a novel method for the Vietnamese-Chinese word alignment which merges a variety of feature constraint models. In this article, an improved model based on the Vietnamese-Chinese progressive structure and offset features of word sequence is described. From this model which is trained by a log-linear model framework, and with parameters trained by the minimum error rate algorithm, the result of the Vietnamese-Chinese auto-alignment is obtained. The basic model of the experiments is IBM Model 3, and as experimental results suggest, this bilingual word alignment method for Vietnamese and Chinese performs well and precision, recall rates are increased by 28.57 and 25.02 %, AER is reduced by 14.25 %.
Vorheriger Artikel A matrix factorization approach to graph compression with partial information
Nächster Artikel Road crack detection using color variance distribution and discriminant analysis for approaching smooth vehicle movement on non-smooth roads

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Metadaten
Titel
A bilingual word alignment algorithm of Vietnamese-Chinese based on feature constraint
verfasst von
Yuanyuan Mo
Jianyi Guo
Zhengtao Yu
Lin Luo
Shengxiang Gao
Publikationsdatum
01.08.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 4/2015
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-014-0293-6

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