Diversity-aware Recommendation

Diversity-Aware Recommendation is a recommendation approach that, as a member of the class of personalized recommendation methods, explicitly incorporates measures to promote variety among recommended items in order to mitigate redundancy and broaden user exposure beyond narrow preferences.

252

Publications

13.7K

Citations

703

Authors

299

Institutions

Publications per year

2017–2026

135

Authors

703

  1. PB
    Peter Brusilovsky

    University of Pittsburgh, United States

    5 publications · 172 citations

    5

    h-index

  2. TZ
    Tao Zhou

    University of Electronic Science and Technology of China, China

    5 publications · 1.4K citations

    5

    h-index

  3. NH
    Neil Hurley

    University College Dublin, Ireland

    5 publications · 563 citations

    5

    h-index

  4. MS
    Markus Schedl

    Johannes Kepler University of Linz, Austria

    5 publications · 144 citations

    5

    h-index

  5. GA
    Gediminas Adomavičius

    University of Minnesota, United States

    4 publications · 859 citations

    4

    h-index

1–5 of 703

Venues

  1. Knowledge-Based Systems

    9 publications · 790 citations

    9

    h-index

  2. arXiv (Cornell University)

    Repository · 8 publications · 256 citations

    8

    h-index

  3. ACM Transactions on Information Systems

    4 publications · 107 citations

    4

    h-index

  4. Knowledge and Information Systems

    3 publications · 153 citations

    3

    h-index

  5. Expert Systems with Applications

    3 publications · 101 citations

    3

    h-index

1–5