User Fairness

User Fairness is a fairness criterion in recommendation systems that ensures equitable treatment or outcomes for individual users by mitigating biases in personalization processes that may systematically disadvantage certain users based on sensitive attributes or positional advantages.

370

Publications

25.8K

Citations

1.1K

Authors

389

Institutions

Publications per year

2017–2026

246

Authors

1.1K

  1. ZD
    Zhiguo Ding

    University of Manchester, United Kingdom

    13 publications · 1.4K citations

    13

    h-index

  2. RB
    Robin Burke

    DePaul University, United States

    11 publications · 422 citations

    10

    h-index

  3. OA
    Octavia A. Dobre

    Memorial University of Newfoundland, Canada

    7 publications · 957 citations

    7

    h-index

  4. YZ
    Yongfeng Zhang

    Rutgers, The State University of New Jersey, United States

    6 publications · 501 citations

    6

    h-index

  5. HV
    H. Vincent Poor

    Princeton University, United States

    6 publications · 1.3K citations

    6

    h-index

1–5 of 1.1K

Venues

  1. IEEE Transactions on Wireless Communications

    24 publications · 2.8K citations

    21

    h-index

  2. IEEE Transactions on Vehicular Technology

    17 publications · 1.1K citations

    15

    h-index

  3. arXiv (Cornell University)

    Repository · 16 publications · 614 citations

    14

    h-index

  4. IEEE Transactions on Communications

    13 publications · 1.1K citations

    13

    h-index

  5. IEEE Access

    16 publications · 455 citations

    13

    h-index

1–5