Learning method for automatic acquisition of translation knowledge
被引:0
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作者:
Echizen-ya, H
论文数: 0引用数: 0
h-index: 0
机构:Hokkai Gakuen Univ, Dept Elect & Informat, Chuo Ku, Sapporo, Hokkaido 0640926, Japan
Echizen-ya, H
Araki, K
论文数: 0引用数: 0
h-index: 0
机构:Hokkai Gakuen Univ, Dept Elect & Informat, Chuo Ku, Sapporo, Hokkaido 0640926, Japan
Araki, K
Momouchi, Y
论文数: 0引用数: 0
h-index: 0
机构:Hokkai Gakuen Univ, Dept Elect & Informat, Chuo Ku, Sapporo, Hokkaido 0640926, Japan
Momouchi, Y
机构:
[1] Hokkai Gakuen Univ, Dept Elect & Informat, Chuo Ku, Sapporo, Hokkaido 0640926, Japan
[2] Hokkaido Univ, Grad Sch Informat Sci & Technol, Kita Ku, Sapporo, Hokkaido 0600814, Japan
来源:
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS
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2005年
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3682卷
关键词:
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
This paper presents a new learning method for automatic acquisition of translation knowledge from parallel corpora, We apply this learning method to automatic extraction of bilingual word pairs from parallel corpora. In general, similarity measures are used to extract bilingual word pairs from parallel corpora. However, similarity measures are insufficient because of the sparse data problem. The essence of our learning method is this presumption: in local parts of bilingual sentence pairs, the equivalents of words that adjoin the source language words of bilingual word pairs also adjoin the target language words of bilingual word pairs. Such adjacent information is acquired automatically in our method. We applied our method to systems based on various similarity measures, thereby confirming the effectiveness of our method.