Graph-based Sequential Recommendation

Graph-Based Sequential Recommendation is a sequential recommendation framework that models user-item interactions and item transitions as a graph structure to capture complex, high-order dependencies and semantic relations among items for more accurate next-item prediction.

43

Publications

2.3K

Citations

180

Authors

77

Institutions

Publications per year

2017–2026

42

Authors

180

  1. YL
    Yong Liu

    Nanyang Technological University, Singapore

    4 publications · 273 citations

    4

    h-index

  2. LG
    Lei Guo

    Shandong Normal University, China

    3 publications · 175 citations

    3

    h-index

  3. LZ
    Lei Zhu

    Shandong Normal University, China

    3 publications · 175 citations

    3

    h-index

  4. TC
    Tong Chen

    The University of Queensland, Australia

    3 publications · 175 citations

    3

    h-index

  5. HY
    Hongzhi Yin

    The University of Queensland, Australia

    3 publications · 175 citations

    3

    h-index

1–5 of 180

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 3 publications · 333 citations

    3

    h-index

  2. ACM Transactions on Information Systems

    5 publications · 147 citations

    3

    h-index

  3. Information Processing & Management

    3 publications · 112 citations

    3

    h-index

  4. World Wide Web

    2 publications · 93 citations

    2

    h-index

  5. 1

    h-index

1–5