Rule-based Negation Detection

Rule-Based Negation Detection is a negation detection method that identifies and classifies negated elements in text through the application of manually crafted linguistic rules specifying patterns of negation cues and their scope.

35

Publications

1.7K

Citations

102

Authors

63

Institutions

Publications per year

2017–2026

14

Authors

102

  1. DN
    Dirk Neumann

    University of Freiburg, Germany

    3 publications · 86 citations

    3

    h-index

  2. NP
    Nicolas Pröllochs

    Ludwig-Maximilians-Universität München, Germany

    3 publications · 86 citations

    3

    h-index

  3. SF
    Stefan Feuerriegel

    ETH Zurich, Switzerland

    3 publications · 86 citations

    3

    h-index

  4. MB
    Mohammadhadi Bagheri

    National Institutes of Health Clinical Center, United States

    2 publications · 242 citations

    2

    h-index

  5. JC
    Jorge Carrillo‐de‐Albornoz

    Universidad Nacional de Educación a Distancia, Spain

    2 publications · 51 citations

    2

    h-index

1–5 of 102

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 161 citations

    2

    h-index

  2. Journal of the American Medical Informatics Association

    JAMIA · 2 publications · 351 citations

    2

    h-index

  3. Natural Language Engineering

    2 publications · 48 citations

    2

    h-index

  4. IEEE Access

    1 publications · 38 citations

    1

    h-index

  5. Joint Conference on Lexical and Computational Semantics

    Conference · 1 publications · 40 citations

    1

    h-index

1–5