Trust-aware Matrix Factorization

Trust-Aware Matrix Factorization is a matrix factorization-based recommendation method that incorporates user trust relationships into the latent factor model to enhance prediction accuracy by jointly modeling user-item interactions and user-to-user trust propagation.

20

Publications

5.2K

Citations

77

Authors

49

Institutions

Publications per year

2017–2026

12

Authors

77

  1. GG
    Guibing Guo

    Northeastern University, China

    2 publications · 602 citations

    2

    h-index

  2. HM
    Hao Ma

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 1.9K citations

    2

    h-index

  3. JM
    Jianhua Ma

    Hosei University, Japan

    2 publications · 85 citations

    2

    h-index

  4. MR
    Michael R. Lyu

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 1.9K citations

    2

    h-index

  5. RH
    Runhe Huang

    Hosei University, Japan

    2 publications · 85 citations

    2

    h-index

1–5 of 77

Venues

  1. IEEE Access

    2 publications · 32 citations

    2

    h-index

  2. 1

    h-index

  3. Knowledge-Based Systems

    1 publications · 71 citations

    1

    h-index

  4. 1

    h-index

  5. Neurocomputing

    1 publications · 19 citations

    1

    h-index

1–5