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Translation of technical terminologies between English and Korean based on textual big data
Author(s) -
Kim Taehong,
Hwang Myunggwon,
Hwang MiNyeong,
Song Sakwang,
Jeong DoHeon,
Jung Hanmin
Publication year - 2015
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2284
Subject(s) - computer science , terminology , natural language processing , reliability (semiconductor) , information retrieval , quality (philosophy) , machine translation , big data , artificial intelligence , translation (biology) , linguistics , data mining , philosophy , power (physics) , physics , biochemistry , chemistry , epistemology , quantum mechanics , messenger rna , gene
Summary A number of web applications provide completely automated machine translation services, allowing users to easily translate information of interest. However, these services still generate inaccurate results when translating technical terminologies. Therefore, we propose a new method that collects reliable pairs of English–Korean technical terms and translates the given English terminology to Korean. To collect the pairs, we utilize textual big data, such as Korean academic papers, and develop a new statistical model to determine appropriate characteristics. Our method is evaluated in terms of the reliability of English–Korean pairs and the precision of translation. We thus confirm that our method can produce highly reliable data and can positively influence the translation quality of technical terminologies. Copyright © 2014 John Wiley & Sons, Ltd.