Hybrid Filtering

Hybrid Filtering is a filtering approach that integrates multiple distinct information filtering techniques—such as collaborative, content-based, and knowledge-based methods—within a unified framework to overcome the limitations of individual approaches and improve overall recommendation accuracy and robustness.

281

Publications

15.8K

Citations

795

Authors

341

Institutions

Publications per year

2017–2026

111

Authors

795

  1. LJ
    Leontios J. Hadjileontiadis

    Aristotle University of Thessaloniki, Greece

    3 publications · 337 citations

    3

    h-index

  2. BM
    Byeong Man Kim

    Kumoh National Institute of Technology, South Korea

    3 publications · 352 citations

    3

    h-index

  3. QL
    Qing Li

    City University of Hong Kong, Hong Kong SAR China

    3 publications · 352 citations

    3

    h-index

  4. BJ
    Beth Jelfs

    RMIT University, Australia

    3 publications · 64 citations

    3

    h-index

  5. NK
    Nikos Karacapilidis

    University of Patras, Greece

    1 publications · 17 citations

    2

    h-index

1–5 of 795

Venues

  1. IEEE Access

    10 publications · 746 citations

    11

    h-index

  2. Expert Systems with Applications

    7 publications · 664 citations

    7

    h-index

  3. Information Sciences

    4 publications · 655 citations

    4

    h-index

  4. International Journal of Computer Applications

    3 publications · 338 citations

    3

    h-index

  5. Sensors

    3 publications · 71 citations

    3

    h-index

1–5