Ranking Metrics

Ranking Metrics is a computational evaluation framework used in recommender systems that quantifies the effectiveness of ranked item lists by measuring the position and relevance of recommended items relative to user preferences.

505

Publications

57K

Citations

1.4K

Authors

529

Institutions

Publications per year

2017–2026

204

Variants

Ranking Evaluation Metrics

Authors

1.4K

  1. AB
    Alejandro Bellogín

    Universidad Autónoma de Madrid, Spain

    12 publications · 925 citations

    11

    h-index

  2. PC
    Pablo Castells

    Universidad Autónoma de Madrid, Spain

    8 publications · 701 citations

    8

    h-index

  3. JR
    John Riedl

    University of Minnesota, United States

    8 publications · 9.3K citations

    8

    h-index

  4. JA
    Joseph A. Konstan

    University of Minnesota, United States

    7 publications · 9K citations

    7

    h-index

  5. MD
    Michael D. Ekstrand

    Boise State University, United States

    7 publications · 572 citations

    7

    h-index

1–5 of 1.4K

Venues

  1. Expert Systems with Applications

    13 publications · 679 citations

    13

    h-index

  2. arXiv (Cornell University)

    Repository · 13 publications · 400 citations

    11

    h-index

  3. Knowledge-Based Systems

    10 publications · 794 citations

    10

    h-index

  4. Information Sciences

    9 publications · 661 citations

    9

    h-index

  5. Journal of Business Research

    JBR · 5 publications · 778 citations

    5

    h-index

1–5