Salience Estimation

Salience Estimation is a computational method in keyword extraction that identifies and ranks terms based on their prominence and relevance within a document relative to a broader corpus, distinguishing itself by quantifying term importance through statistical and contextual cues rather than frequency alone.

138

Publications

9.9K

Citations

385

Authors

182

Institutions

Publications per year

2017–2026

39

Authors

385

  1. CA
    Christopher A. Cooper

    Western Carolina University, United States

    3 publications · 133 citations

    3

    h-index

  2. DR
    Dennis R. Proffítt

    University of Virginia, United States

    2 publications · 152 citations

    2

    h-index

  3. MD
    Mieke Donk

    Vrije Universiteit Amsterdam, Netherlands

    2 publications · 205 citations

    2

    h-index

  4. FW
    Fei Wang

    Cornell University, United States

    2 publications · 38 citations

    2

    h-index

  5. PW
    Peter Wenderoth

    The University of Sydney, Australia

    2 publications · 89 citations

    2

    h-index

1–5 of 385

Venues

  1. Frontiers in Psychology

    5 publications · 308 citations

    5

    h-index

  2. Journal of Vision

    5 publications · 302 citations

    5

    h-index

  3. Political Research Quarterly

    PRQ · 4 publications · 184 citations

    4

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 108 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 160 citations

    3

    h-index

1–5