Cross-domain Collaborative Filtering

Cross-Domain Collaborative Filtering is a collaborative filtering approach that transfers user preference knowledge across distinct but related domains to improve recommendation accuracy in a target domain by leveraging auxiliary data from a source domain.

78

Publications

4.4K

Citations

219

Authors

94

Institutions

Publications per year

2017–2026

41

Variants

Cdcf

Authors

219

  1. XY
    Xu Yu

    Qingdao University of Science and Technology, China

    5 publications · 450 citations

    5

    h-index

  2. QY
    Qiang Yang

    Hong Kong University of Science and Technology, Hong Kong SAR China

    5 publications · 1K citations

    5

    h-index

  3. FJ
    Feng Jiang

    Qingdao University of Science and Technology, China

    5 publications · 450 citations

    5

    h-index

  4. JD
    Junwei Du

    Qingdao University of Science and Technology, China

    4 publications · 292 citations

    4

    h-index

  5. BL
    Bin Li

    Fudan University, China

    4 publications · 793 citations

    4

    h-index

1–5 of 219

Venues

  1. IEEE Access

    6 publications · 182 citations

    6

    h-index

  2. Expert Systems with Applications

    2 publications · 69 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 1 publications · 98 citations

    2

    h-index

  4. Procedia Computer Science

    2 publications · 22 citations

    2

    h-index

  5. Information Sciences

    2 publications · 71 citations

    2

    h-index

1–5