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Application of the Search Engine Google as Big Data in Translation Studies
번역 연구에서 빅코퍼스로서의 구글 활용

  • 간행물
    한국외국어대학교 통번역연구소 학술대회 바로가기
  • 권호(발행년)
    제18회 ITRI-GSIT 국제 학술대회 (2018.01) 바로가기
  • 페이지
    pp.151-161
  • 저자
    Cho Joon-Hyung, Lee Hye-Won
  • 언어
    한국어(KOR)
  • URL
    https://www.earticle.net/Article/A333513

원문정보

초록

영어
From the 1960s, the corpus became the resources in the field of linguistics for the practical studies. Translation studies also accepted this type of study to explain translational phenomena. Since Gideon Toury and Mona Baker proposed the application of corpus in this field, various translation corpora are used to extract translational correspondences for several studies such as translational comparison between two languages, translation education, machine translation, etc. However, a complete corpus needs a lot of time and cost. Moreover, in Korea, there is no big corpus of translation like the website Linguee. From this point of view, we can consider the search engine Google as Big Corpus. Although it is not a parallel corpus, we are able to profit translational correspondences from Google as Big corpus because it may provide quite a number of textual translation resources between Korean and other languages.

목차

Corpus & Translation Studies
 Translation Corpus
 국내코퍼스 연구환경의 현실적인 문제
 코퍼스 연구에서 코퍼스 크기
 코퍼스로서의 검색 엔진
 구글에서 Petit + Prince 번역 조합 탐색
 English Translation of word petit
 구글의 한계

저자

  • Cho Joon-Hyung [ 조준형 | Korea University ]
  • Lee Hye-Won [ 이혜원 | Korea University ]

참고문헌

자료제공 : 네이버학술정보

    간행물 정보

    • 간행물
      한국외국어대학교 통번역연구소 학술대회
    • 간기
      반년간
    • 수록기간
      2016~2026
    • 십진분류
      KDC 717 DDC 400