Machine-readable Dictionaries

Machine-Readable Dictionaries is a computational linguistic resource that consists of structured lexical databases designed for automatic processing by computers, distinguished from traditional dictionaries by their encoded, parseable formats enabling direct use in natural language processing tasks.

149

Publications

8.1K

Citations

284

Authors

138

Institutions

Publications per year

2017–2026

13

Authors

284

  1. NI
    Nancy Ide

    Vassar College, United States

    7 publications · 328 citations

    7

    h-index

  2. JV
    Jean Véronis

    Vassar College, United States

    7 publications · 328 citations

    7

    h-index

  3. TB
    Ted Briscoe

    University of Cambridge, United Kingdom

    4 publications · 265 citations

    4

    h-index

  4. LV
    Lucy Vanderwende

    Microsoft (United States), United States

    4 publications · 283 citations

    4

    h-index

  5. JL
    Judith L. Klavans

    Columbia University, United States

    4 publications · 195 citations

    4

    h-index

1–5 of 284

Venues

  1. International Journal of Lexicography

    IJL · 9 publications · 266 citations

    9

    h-index

  2. Literary and Linguistic Computing

    LLC · 5 publications · 893 citations

    5

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 48 citations

    3

    h-index

  4. HAL (Le Centre pour la Communication Scientifique Directe)

    Repository · 2 publications · 43 citations

    2

    h-index

  5. Computers and the Humanities

    2 publications · 35 citations

    2

    h-index

1–5