Ranking Aggregation Algorithms

Ranking Aggregation Algorithms is a computational methodology that synthesizes multiple individual rankings into a single consensus ranking by minimizing disagreement or optimizing agreement across ranked lists, distinguishing it from other ranking techniques through its focus on integrating heterogeneous or conflicting ordinal preferences into a unified output.

175

Publications

14.2K

Citations

419

Authors

233

Institutions

Publications per year

2017–2026

50

Variants

Rank Aggregation Algorithms

Authors

419

  1. JA
    José A. Gámez

    University of Castilla-La Mancha, Spain

    5 publications · 134 citations

    5

    h-index

  2. JA
    Juan A. Aledo

    University of Castilla-La Mancha, Spain

    5 publications · 134 citations

    5

    h-index

  3. SC
    Stéphan Clémençon

    Laboratoire Traitement et Communication de l’Information, France

    4 publications · 100 citations

    4

    h-index

  4. DS
    Devavrat Shah

    Massachusetts Institute of Technology, United States

    4 publications · 420 citations

    4

    h-index

  5. NA
    Nir Ailon

    Technion – Israel Institute of Technology, Israel

    4 publications · 970 citations

    4

    h-index

1–5 of 419

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 256 citations

    5

    h-index

  2. Expert Systems with Applications

    5 publications · 200 citations

    5

    h-index

  3. Information Sciences

    4 publications · 137 citations

    4

    h-index

  4. Proceedings of the VLDB Endowment

    PVLDB · 3 publications · 248 citations

    3

    h-index

  5. European Journal of Operational Research

    3 publications · 88 citations

    3

    h-index

1–5