Hybrid Recommendation

Hybrid Recommendation is a recommendation approach that combines multiple recommendation techniques or data sources within a unified framework to improve predictive accuracy and robustness beyond the capabilities of any single method.

1.5K

Publications

98.1K

Citations

4.5K

Authors

1.3K

Institutions

Publications per year

2017–2026

879

Authors

4.5K

  1. JL
    Jie Lü

    University of Technology Sydney, Australia

    12 publications · 926 citations

    12

    h-index

  2. IC
    Iván Cantador

    Universidad Autónoma de Madrid, Spain

    11 publications · 1K citations

    11

    h-index

  3. QY
    Qusai Y. Shambour

    Al-Ahliyya Amman University, Jordan

    10 publications · 560 citations

    10

    h-index

  4. PB
    Peter Brusilovsky

    University of Pittsburgh, United States

    10 publications · 898 citations

    10

    h-index

  5. MS
    Markus Schedl

    Johannes Kepler University of Linz, Austria

    10 publications · 506 citations

    10

    h-index

1–5 of 4.5K

Venues

  1. Expert Systems with Applications

    44 publications · 3.2K citations

    28

    h-index

  2. IEEE Access

    56 publications · 2.5K citations

    28

    h-index

  3. Information Sciences

    25 publications · 2.3K citations

    23

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 22 publications · 12K citations

    19

    h-index

  5. Knowledge-Based Systems

    18 publications · 1.6K citations

    18

    h-index

1–5