Sequential Cross-domain Recommendation

Sequential Cross-Domain Recommendation is a cross-domain recommendation paradigm that leverages sequential user behavior patterns across domains to model dynamic preference transitions and improve recommendation accuracy by capturing temporal dependencies in user-item interactions.

23

Publications

1K

Citations

87

Authors

25

Institutions

Publications per year

2017–2026

23

Variants

Scdr

Authors

87

  1. LG
    Lei Guo

    Shandong Normal University, China

    4 publications · 228 citations

    4

    h-index

  2. TC
    Tong Chen

    The University of Queensland, Australia

    4 publications · 228 citations

    4

    h-index

  3. HY
    Hongzhi Yin

    The University of Queensland, Australia

    4 publications · 228 citations

    4

    h-index

  4. LZ
    Lei Zhu

    Shandong Normal University, China

    3 publications · 175 citations

    3

    h-index

  5. MM
    Muyang Ma

    Shandong University, China

    3 publications · 224 citations

    3

    h-index

1–5 of 87

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 112 citations

    2

    h-index

  2. Journal of Computer Science and Technology

    1 publications · 14 citations

    1

    h-index

  3. 1

    h-index

  4. 1

    h-index

  5. 1

    h-index

1–5