Dynamic Graph Clustering

Dynamic Graph Clustering is a computational framework that partitions a time-evolving graph into coherent substructures by identifying and tracking clusters of nodes whose connectivity patterns change over time.

38

Publications

2K

Citations

119

Authors

59

Institutions

Publications per year

2017–2026

14

Variants

Temporal Graph Clustering

Authors

119

  1. JC
    Jie Cao

    Nanjing University of Finance and Economics, China

    2 publications · 160 citations

    2

    h-index

  2. RG
    Robert Görke

    Karlsruhe Institute of Technology, Germany

    2 publications · 43 citations

    2

    h-index

  3. FF
    Francesco Folino

    Institute for High Performance Computing and Networking, Italy

    2 publications · 319 citations

    2

    h-index

  4. CP
    Clara Pizzuti

    Institute for High Performance Computing and Networking, Italy

    2 publications · 319 citations

    2

    h-index

  5. HL
    Hui‐Jia Li

    Central University of Finance and Economics, China

    2 publications · 160 citations

    2

    h-index

1–5 of 119

Venues

  1. Journal of Graph Algorithms and Applications

    JGAA · 2 publications · 114 citations

    2

    h-index

  2. IEEE Symposium on Information Visualization

    Conference · 2 publications · 155 citations

    2

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 94 citations

    2

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 283 citations

    2

    h-index

  5. Computer Graphics Forum

    1 publications · 26 citations

    1

    h-index

1–5