N-gram Features

N-Gram Features is a type of text feature representation in natural language processing that captures contiguous sequences of n items—such as characters, syllables, words, or tokens—from a given corpus, distinguishing itself by its reliance on local sequential order and fixed-length context windows to model lexical and syntactic patterns.

391

Publications

18.9K

Citations

1.1K

Authors

402

Institutions

Publications per year

2017–2026

159

Authors

1.1K

  1. MS
    Murat Saraçlar

    Boğaziçi University, Türkiye

    6 publications · 131 citations

    6

    h-index

  2. AG
    Alexander Gelbukh

    Instituto Politécnico Nacional, Mexico

    6 publications · 530 citations

    6

    h-index

  3. GS
    Grigori Sidorov

    Instituto Politécnico Nacional, Mexico

    4 publications · 405 citations

    4

    h-index

  4. IS
    Izhak Shafran

    Oregon Health & Science University, United States

    4 publications · 94 citations

    4

    h-index

  5. GK
    Grzegorz Kondrak

    University of Alberta, Canada

    4 publications · 127 citations

    4

    h-index

1–5 of 1.1K

Venues

  1. arXiv (Cornell University)

    Repository · 14 publications · 703 citations

    12

    h-index

  2. IEEE Access

    10 publications · 476 citations

    10

    h-index

  3. International Conference on Computational Linguistics

    Conference · 6 publications · 113 citations

    6

    h-index

  4. Procedia Computer Science

    5 publications · 593 citations

    5

    h-index

  5. 4

    h-index

1–5