An Automatic Extraction of English-Korean Bilingual Terms by Using Word-level Presumptive Alignment


KIPS Transactions on Software and Data Engineering, Vol. 2, No. 6, pp. 433-442, Jun. 2013
10.3745/KTSDE.2013.2.6.433,   PDF Download:

Abstract

A set of bilingual terms is one of the most important factors in building language-related applications such as a machine translation system and a cross-lingual information system. In this paper, we introduce a new approach that automatically extracts candidates of English-Korean bilingual terms by using a bilingual parallel corpus and a basic English-Korean lexicon. This approach can be useful even though the size of the parallel corpus is small. A sentence alignment is achieved first for the document-level parallel corpus. We can align words between a pair of aligned sentences by referencing a basic bilingual lexicon. For unaligned words between a pair of aligned sentences, several assumptions are applied in order to align bilingual term candidates of two languages, A location of a sentence, a relation between words, and linguistic information between two languages are examples of the assumptions. An experimental result shows approximately 71.7% accuracy for the English-Korean bilingual term candidates which are automatically extracted from 1,000 bilingual parallel corpus.


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Cite this article
[IEEE Style]
K. J. Lee, "An Automatic Extraction of English-Korean Bilingual Terms by Using Word-level Presumptive Alignment," KIPS Transactions on Software and Data Engineering, vol. 2, no. 6, pp. 433-442, 2013. DOI: 10.3745/KTSDE.2013.2.6.433.

[ACM Style]
Kong Joo Lee. 2013. An Automatic Extraction of English-Korean Bilingual Terms by Using Word-level Presumptive Alignment. KIPS Transactions on Software and Data Engineering, 2, 6, (2013), 433-442. DOI: 10.3745/KTSDE.2013.2.6.433.