Iteratively constrained selection of word alignment links using knowledge and statistics

被引：1

作者：

Lee, Jonghoon ^{[1
]}

Lee, Sungjin ^{[1
]}

Noh, Hyeongjong ^{[1
]}

Lee, Kyusong ^{[1
]}

Lee, Gary Geunbae ^{[1
]}

机构：

[1] Pohang Univ Sci & Technol, Dept Comp Sci & Engn, Pohang, South Korea

来源：

KNOWLEDGE-BASED SYSTEMS | 2011年 / 24卷 / 07期

关键词：

Bilingual resource; Parallel text; Machine translation; Word alignment; Korean-English;

D O I：

10.1016/j.knosys.2011.05.012

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Word alignment is a crucial component in applications that use bilingual resources. Statistical methods are widely used because they are portable and allow simple system building. However, pure statistical methods often incorrectly align functional words in the English-Korean language pair due to differences in the typology of the languages and a lack of knowledge. Knowledge is inevitably required to correct errors and to improve word alignment quality. In this paper, we introduce an effective method that uses an iterative process to incorporate knowledge into the word alignment system. The method achieved significant improvements in word alignment and its application: statistical machine translation. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：1120 / 1130

页数：11