Diversity Optimization

Diversity Optimization is a recommendation system objective that enhances the variety of suggested items by explicitly prioritizing the inclusion of dissimilar or complementary options beyond mere relevance to the user.

133

Publications

9.9K

Citations

371

Authors

212

Institutions

Publications per year

2017–2026

50

Authors

371

  1. FN
    Frank Neumann

    The University of Adelaide, Australia

    5 publications · 118 citations

    5

    h-index

  2. AD
    Abraham Duarte

    Universidad Rey Juan Carlos, Spain

    5 publications · 494 citations

    5

    h-index

  3. MG
    Micael Gallego

    Universidad Rey Juan Carlos, Spain

    3 publications · 242 citations

    3

    h-index

  4. AN
    Aneta Neumann

    The University of Adelaide, Australia

    3 publications · 50 citations

    3

    h-index

  5. MA
    Mohamed‐Slim Alouini

    King Abdullah University of Science and Technology, Saudi Arabia

    3 publications · 221 citations

    3

    h-index

1–5 of 371

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 183 citations

    4

    h-index

  2. Proceedings of the Genetic and Evolutionary Computation Conference

    Conference · 4 publications · 65 citations

    4

    h-index

  3. Information Sciences

    4 publications · 213 citations

    4

    h-index

  4. European Journal of Operational Research

    4 publications · 322 citations

    4

    h-index

  5. IEEE Transactions on Evolutionary Computation

    4 publications · 819 citations

    4

    h-index

1–5