Abstract
Numerous methods have been developed for generating a machine translation (MT) bilingual dictionary from a parallel text corpus. Such methods extract bilingual collocations from sentence pairs of source and target language sentences. Then those collocations are registered in an MT bilingual dictionary. Bilingual collocations are lexically corresponding pairs of parts extracted from sentence pairs. This paper describes a new method for automatic extraction of bilingual collocations from a parallel text corpus using no linguistic knowledge. We use Recursive Chain-link-type Learning (RCL), which is a learning algorithm, to extract bilingual collocations. Our method offers two main advantages. One benefit is that this RCL system requires no linguistic knowledge. The other advantage is that it can extract many bilingual collocations, even if the frequency of appearance of the bilingual collocations is very low. Experimental results verify that our system extracts bilingual collocations efficiently. The extraction rate of bilingual collocations was 74.9% for all bilingual collocations that corresponded to nouns in the parallel corpus.
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© 2004 Springer-Verlag Berlin Heidelberg
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Echizen-ya, H., Araki, K., Momouchi, Y., Tochinai, K. (2004). Automatic Building of a Machine Translation Bilingual Dictionary Using Recursive Chain-Link-Type Learning from a Parallel Corpus. In: Monroy, R., Arroyo-Figueroa, G., Sucar, L.E., Sossa, H. (eds) MICAI 2004: Advances in Artificial Intelligence. MICAI 2004. Lecture Notes in Computer Science(), vol 2972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24694-7_42
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DOI: https://doi.org/10.1007/978-3-540-24694-7_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21459-5
Online ISBN: 978-3-540-24694-7
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