Graph-based Modeling

Graph-Based Modeling is a topological modeling approach that represents entities as nodes and their relationships as edges within a graph structure, enabling the analysis of relational and structural patterns in data.

387

Publications

23.9K

Citations

1.2K

Authors

462

Institutions

Publications per year

2017–2026

161

Authors

1.2K

  1. AG
    Andrew G. Alleyne

    University of Illinois Urbana-Champaign, United States

    6 publications · 130 citations

    7

    h-index

  2. VM
    Ví­ctor M. Zavala

    University of Wisconsin–Madison, United States

    4 publications · 125 citations

    5

    h-index

  3. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    5 publications · 248 citations

    5

    h-index

  4. HC
    Herschel C. Pangborn

    University of Illinois Urbana-Champaign, United States

    4 publications · 103 citations

    4

    h-index

  5. CJ
    Christopher Jones

    National Institute for Biological Standards and Control, United Kingdom

    3 publications · 188 citations

    3

    h-index

1–5 of 1.2K

Venues

  1. arXiv (Cornell University)

    Repository · 13 publications · 296 citations

    12

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 237 citations

    6

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 6 publications · 230 citations

    6

    h-index

  4. 4

    h-index

  5. ACM Transactions on Knowledge Discovery from Data

    TKDD · 2 publications · 48 citations

    3

    h-index

1–5