Subgraph Features

Subgraph Features is a graph-level representation learning technique that extracts discriminative structural patterns by identifying and encoding recurrent subgraph motifs or substructures within a larger graph, thereby distinguishing it from node- or edge-level feature extraction methods.

130

Publications

7.7K

Citations

442

Authors

186

Institutions

Publications per year

2017–2026

69

Authors

442

  1. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    11 publications · 828 citations

    11

    h-index

  2. XZ
    Xingquan Zhu

    Florida Atlantic University, United States

    10 publications · 664 citations

    10

    h-index

  3. CZ
    Chengqi Zhang

    University of Technology Sydney, Australia

    11 publications · 658 citations

    10

    h-index

  4. JW
    Jia Wu

    Macquarie University, Australia

    8 publications · 626 citations

    8

    h-index

  5. SP
    Shirui Pan

    Monash University, Australia

    8 publications · 395 citations

    8

    h-index

1–5 of 442

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 1.3K citations

    11

    h-index

  2. 8

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 7 publications · 442 citations

    7

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 184 citations

    4

    h-index

  5. Knowledge-Based Systems

    3 publications · 185 citations

    3

    h-index

1–5