Recommendation Engines

Recommendation Engines is a computational system that personalizes user experiences by predicting and suggesting relevant items or content based on individual preferences, behavioral patterns, and contextual data.

392

Publications

27.7K

Citations

1.2K

Authors

411

Institutions

Publications per year

2017–2026

165

Authors

1.2K

  1. JB
    Joeran Beel

    Trinity College Dublin, Ireland

    5 publications · 128 citations

    5

    h-index

  2. JR
    John Riedl

    University of Minnesota, United States

    4 publications · 2.6K citations

    5

    h-index

  3. JA
    Joseph A. Konstan

    University of Minnesota, United States

    4 publications · 6.4K citations

    5

    h-index

  4. MX
    Michelle X. Zhou

    IBM (United States), United States

    4 publications · 129 citations

    4

    h-index

  5. BG
    Béla Gipp

    University of Konstanz, Germany

    4 publications · 74 citations

    4

    h-index

1–5 of 1.2K

Venues

  1. Expert Systems with Applications

    11 publications · 657 citations

    11

    h-index

  2. arXiv (Cornell University)

    Repository · 6 publications · 141 citations

    7

    h-index

  3. Procedia Computer Science

    4 publications · 169 citations

    5

    h-index

  4. SSRN Electronic Journal

    Repository · 4 publications · 175 citations

    5

    h-index

  5. Proceedings of the VLDB Endowment

    PVLDB · 4 publications · 116 citations

    4

    h-index

1–5