Motion Pattern Mining

Motion Pattern Mining is a computational methodology within traffic behavior analysis that identifies and extracts recurring spatiotemporal movement regularities of traffic participants from trajectory data to model and predict their future motions.

69

Publications

3.6K

Citations

222

Authors

103

Institutions

Publications per year

2017–2026

21

Authors

222

  1. RK
    Roland Kays

    North Carolina Museum of Natural Sciences, United States

    4 publications · 563 citations

    4

    h-index

  2. ZL
    Zhenhui Li

    Kunming Medical University, China

    4 publications · 496 citations

    4

    h-index

  3. BD
    Bolin Ding

    Alibaba Group (United States), United States

    3 publications · 473 citations

    3

    h-index

  4. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    3 publications · 524 citations

    3

    h-index

  5. JM
    Ji Ming

    Queen's University Belfast, United Kingdom

    2 publications · 223 citations

    2

    h-index

1–5 of 222

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 5 publications · 239 citations

    5

    h-index

  2. 4

    h-index

  3. IEEE Access

    2 publications · 273 citations

    2

    h-index

  4. ACM Transactions on Intelligent Systems and Technology

    TIST · 2 publications · 148 citations

    2

    h-index

  5. Accident Analysis & Prevention

    2 publications · 96 citations

    2

    h-index

1–5