Diversity Fairness

Diversity Fairness is an academic construct within fairness in recommendation systems that specifies the equitable representation and inclusion of varied user preferences, item categories, or provider groups across recommendation outputs, thereby distinguishing itself from other fairness notions by prioritizing heterogeneity and coverage as a means to mitigate monocultural or homogenized filtering.

7

Publications

398

Citations

16

Authors

11

Institutions

Publications per year

2017–2026

3

Authors

16

  1. YW
    Yanhao Wang

    National University of Singapore, Singapore

    1 publications · 13 citations

    1

    h-index

  2. CS
    Christopher Selvarajah

    Swinburne University of Technology, Australia

    1 publications · 45 citations

    1

    h-index

  3. DR
    Diana Rajendran

    Swinburne University of Technology, Australia

    1 publications · 45 citations

    1

    h-index

  4. CR
    Cheryl R. Kaiser

    University of Washington, United States

    1 publications · 82 citations

    1

    h-index

  5. IB
    Inácio Bó

    University of Lausanne, Switzerland

    1 publications · 28 citations

    1

    h-index

1–5 of 16

Venues

  1. 2022 IEEE 38th International Conference on Data Engineering (ICDE)

    Conference · 1 publications · 13 citations

    1

    h-index

  2. Human Resource Management Journal

    1 publications · 146 citations

    1

    h-index

  3. Social Psychological and Personality Science

    SPPS · 1 publications · 30 citations

    1

    h-index

  4. Games and Economic Behavior

    1 publications · 28 citations

    1

    h-index

  5. 1

    h-index

1–5