Co-occurrence Matrix Factorization

Co-Occurrence Matrix Factorization is a dimensionality reduction technique in natural language processing that factorizes a term-context co-occurrence matrix into lower-dimensional vector representations to capture semantic relationships between words based on their distributional properties.

86

Publications

42.2K

Citations

310

Authors

149

Institutions

Publications per year

2017–2026

26

Authors

310

  1. RC
    Ronan Collobert

    Meta (Israel), Israel

    2 publications · 89 citations

    2

    h-index

  2. AS
    Aghiles Salah

    Université Paris Cité, France

    2 publications · 53 citations

    2

    h-index

  3. RL
    Rémi Lebret

    École Polytechnique Fédérale de Lausanne, Switzerland

    2 publications · 89 citations

    2

    h-index

  4. MN
    Mohamed Nadif

    Université Paris Cité, France

    2 publications · 53 citations

    2

    h-index

  5. JA
    John A. Bullinaria

    University of Birmingham, United Kingdom

    2 publications · 1.1K citations

    2

    h-index

1–5 of 310

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 168 citations

    3

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 125 citations

    3

    h-index

  3. Information Processing & Management

    3 publications · 276 citations

    3

    h-index

  4. Neurocomputing

    2 publications · 46 citations

    2

    h-index

  5. Behavior Research Methods

    BRM · 2 publications · 1.1K citations

    2

    h-index

1–5