Recommendation Diversification

Recommendation Diversification is a recommendation strategy that enhances the variety of suggested items by deliberately reducing redundancy and promoting coverage across different categories, attributes, or user interests within a ranked list.

69

Publications

4.4K

Citations

209

Authors

109

Institutions

Publications per year

2017–2026

31

Variants

Recommender System Diversification

Authors

209

  1. MP
    Mark P. Graus

    Eindhoven University of Technology, Netherlands

    4 publications · 128 citations

    4

    h-index

  2. NH
    Neil Hurley

    University College Dublin, Ireland

    4 publications · 126 citations

    4

    h-index

  3. BF
    Bruce Ferwerda

    Johannes Kepler University of Linz, Austria

    2 publications · 30 citations

    2

    h-index

  4. WZ
    Wen Zheng

    Taiyuan University of Technology, China

    2 publications · 78 citations

    2

    h-index

  5. OK
    Onur Küçüktunç

    The Ohio State University, United States

    2 publications · 81 citations

    2

    h-index

1–5 of 209

Venues

  1. Knowledge-Based Systems

    3 publications · 164 citations

    3

    h-index

  2. Information Processing & Management

    2 publications · 39 citations

    2

    h-index

  3. Multimedia Tools and Applications

    2 publications · 21 citations

    2

    h-index

  4. arXiv (Cornell University)

    Repository · 2 publications · 40 citations

    2

    h-index

  5. TU/e Research Portal

    Repository · 2 publications · 38 citations

    2

    h-index

1–5