Ranking Optimization

Ranking Optimization is a recommendation technique that specifically refines the ordering of items in a user's suggested list by jointly leveraging multiple criteria and dynamic user feedback to maximize relevance and personalization in real-time collaborative filtering systems.

240

Publications

13.9K

Citations

733

Authors

314

Institutions

Publications per year

2017–2026

99

Authors

733

  1. ML
    Martha Larson

    Delft University of Technology, Netherlands

    4 publications · 136 citations

    4

    h-index

  2. YS
    Yue Shi

    Delft University of Technology, Netherlands

    3 publications · 96 citations

    3

    h-index

  3. AH
    Alan Hanjalić

    Delft University of Technology, Netherlands

    3 publications · 96 citations

    3

    h-index

  4. AO
    Abdelaziz Ouadah

    École Nationale Supérieure d'Informatique, Algeria

    3 publications · 74 citations

    3

    h-index

  5. AK
    Alexandros Karatzoglou

    Telefonica Research and Development, Spain

    3 publications · 402 citations

    3

    h-index

1–5 of 733

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 514 citations

    11

    h-index

  2. Expert Systems with Applications

    10 publications · 448 citations

    10

    h-index

  3. Knowledge-Based Systems

    5 publications · 283 citations

    5

    h-index

  4. 5

    h-index

  5. Information Sciences

    5 publications · 395 citations

    5

    h-index

1–5