Informal Text Normalization

Informal Text Normalization is a computational methodology within text normalization that specifically transforms non-standard, colloquial, or user-generated textual variants into standardized forms while preserving semantic accuracy, distinguishing itself from general text normalization by its focus on informal linguistic phenomena such as slang, abbreviations, and orthographic variations.

20

Publications

562

Citations

48

Authors

20

Institutions

Publications per year

2017–2026

5

Authors

48

  1. YL
    Yang Liu

    Nanyang Technological University, Singapore

    4 publications · 154 citations

    4

    h-index

  2. DL
    Deana L. Pennell

    The University of Texas at Dallas, United States

    3 publications · 132 citations

    3

    h-index

  3. KT
    Kapil Thadani

    Columbia University, United States

    1 publications · 13 citations

    1

    h-index

  4. JK
    Jebran Khan

    Korea Aerospace University, South Korea

    1 publications · 17 citations

    1

    h-index

  5. AP
    Aasish Pappu

    Carnegie Mellon University, United States

    1 publications · 13 citations

    1

    h-index

1–5 of 48

Venues

  1. Computer Speech & Language

    1 publications · 34 citations

    1

    h-index

  2. Applied Sciences

    1 publications · 17 citations

    1

    h-index

  3. 1

    h-index

  4. Language Resources and Evaluation

    1 publications · 17 citations

    1

    h-index

  5. 1

    h-index

1–5