Context-aware Matrix Factorization

Context-Aware Matrix Factorization is a matrix factorization framework that extends traditional collaborative filtering by incorporating contextual variables—such as user location, time, or device—into the latent factor model to enable personalized recommendations that dynamically adapt to situational influences.

63

Publications

3.6K

Citations

181

Authors

72

Institutions

Publications per year

2017–2026

29

Authors

181

  1. FR
    Francesco Ricci⋆

    Free University of Bozen-Bolzano, Italy

    6 publications · 616 citations

    6

    h-index

  2. YZ
    Yong Zheng

    Illinois Institute of Technology, United States

    3 publications · 120 citations

    3

    h-index

  3. BM
    Bamshad Mobasher

    DePaul University, United States

    3 publications · 120 citations

    3

    h-index

  4. LB
    Linas Baltrunas

    Telefonica Research and Development, Spain

    3 publications · 564 citations

    3

    h-index

  5. RB
    Robin Burke

    DePaul University, United States

    3 publications · 120 citations

    3

    h-index

1–5 of 181

Venues

  1. Expert Systems with Applications

    2 publications · 41 citations

    2

    h-index

  2. Information Sciences

    2 publications · 91 citations

    2

    h-index

  3. ACM Transactions on Intelligent Systems and Technology

    TIST · 2 publications · 187 citations

    2

    h-index

  4. Future Generation Computer Systems

    FGCS · 2 publications · 183 citations

    2

    h-index

  5. Neurocomputing

    2 publications · 172 citations

    2

    h-index

1–5