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• W2000200471 abstract "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." @default.
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• W2000200471 date "2011-10-01" @default.
• W2000200471 modified "2023-09-27" @default.
• W2000200471 title "Iteratively constrained selection of word alignment links using knowledge and statistics" @default.
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• W2000200471 doi "https://doi.org/10.1016/j.knosys.2011.05.012" @default.
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