Context-aware Collaborative Filtering

Context-Aware Collaborative Filtering is a recommendation approach that extends traditional collaborative filtering by incorporating contextual information—such as time, location, or social environment—into the prediction model to improve recommendation accuracy through context-sensitive user-item interaction analysis.

152

Publications

18.2K

Citations

451

Authors

209

Institutions

Publications per year

2017–2026

64

Authors

451

  1. LB
    Linas Baltrunas

    Telefonica Research and Development, Spain

    6 publications · 1.2K citations

    6

    h-index

  2. DJ
    Dietmar Jannach

    University of Klagenfurt, Austria

    4 publications · 173 citations

    4

    h-index

  3. AT
    Alexander Tuzhilin

    New York University, United States

    4 publications · 10.4K citations

    4

    h-index

  4. WW
    Wolfgang Woerndl

    Technical University of Munich, Germany

    3 publications · 220 citations

    3

    h-index

  5. GA
    Gediminas Adomavičius

    University of Minnesota, United States

    3 publications · 10.4K citations

    3

    h-index

1–5 of 451

Venues

  1. Expert Systems with Applications

    6 publications · 571 citations

    6

    h-index

  2. IEEE Access

    4 publications · 227 citations

    4

    h-index

  3. Multimedia Tools and Applications

    4 publications · 182 citations

    4

    h-index

  4. Information

    2 publications · 34 citations

    2

    h-index

  5. Information Systems

    2 publications · 143 citations

    2

    h-index

1–5