Example-based Machine Translation

Example-Based Machine Translation is a machine translation approach that belongs to the class of data-driven translation methods and is distinguished by its reliance on previously translated sentence pairs or phrases from a bilingual corpus to generate new translations through analogy and adaptation.

114

Publications

3.4K

Citations

215

Authors

63

Institutions

Publications per year

2017–2026

7

Authors

215

  1. AW
    Andy Way

    Dublin City University, Ireland

    16 publications · 506 citations

    13

    h-index

  2. RD
    Ralf D. Brown

    Carnegie Mellon University, United States

    9 publications · 393 citations

    9

    h-index

  3. ES
    Eiichiro Sumita

    National Institute of Information and Communications Technology, Japan

    7 publications · 349 citations

    7

    h-index

  4. AM
    Arul Menezes

    Microsoft (United States), United States

    6 publications · 165 citations

    6

    h-index

  5. SK
    Sadao Kurohashi

    Kyoto University, Japan

    5 publications · 71 citations

    5

    h-index

1–5 of 215

Venues

  1. Arrow@dit (Dublin Institute of Technology)

    Repository · 7 publications · 165 citations

    7

    h-index

  2. Machine Translation

    4 publications · 169 citations

    4

    h-index

  3. ACM Transactions on Asian Language Information Processing

    TALIP · 2 publications · 34 citations

    2

    h-index

  4. Computational Linguistics

    2 publications · 166 citations

    2

    h-index

  5. 2

    h-index

1–5