Long-range Dependency Modeling

Long-Range Dependency Modeling is a computational framework in session-based recommendation systems that captures and leverages temporal dependencies across distant interactions within a session to improve preference prediction, distinguishing itself from short-term modeling approaches by explicitly accounting for non-adjacent item relationships over extended sequences.

219

Publications

28.4K

Citations

903

Authors

252

Institutions

Publications per year

2017–2026

194

Authors

903

  1. SL
    Shujie Liu

    Microsoft Research Asia (China), China

    4 publications · 874 citations

    4

    h-index

  2. YL
    Yanqing Liu

    Jiangnan University, China

    3 publications · 860 citations

    3

    h-index

  3. CS
    Chunhua Shen

    The University of Adelaide, Australia

    3 publications · 304 citations

    3

    h-index

  4. SZ
    Sheng Zhao

    Microsoft Research Asia (China), China

    3 publications · 860 citations

    3

    h-index

  5. GS
    Guanglu Song

    Chinese University of Hong Kong, Hong Kong SAR China

    3 publications · 677 citations

    3

    h-index

1–5 of 903

Venues

  1. arXiv (Cornell University)

    Repository · 43 publications · 8.7K citations

    24

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 10 publications · 7.2K citations

    10

    h-index

  3. 8

    h-index

  4. 5

    h-index

  5. IEEE Transactions on Medical Imaging

    5 publications · 356 citations

    5

    h-index

1–5