Path-based Features

Path-Based Features is a graph feature engineering method that derives node or graph representations by analyzing structural and semantic characteristics of paths—such as shortest, random, or contextual walks—within a graph, thereby distinguishing itself from node- or edge-centric approaches through its focus on relational sequences.

64

Publications

3.5K

Citations

215

Authors

106

Institutions

Publications per year

2017–2026

34

Authors

215

  1. LJ
    Lianwen Jin

    South China University of Technology, China

    3 publications · 113 citations

    3

    h-index

  2. WY
    Weixin Yang

    South China University of Technology, China

    3 publications · 113 citations

    3

    h-index

  3. RB
    Regina Barzilay

    Massachusetts Institute of Technology, United States

    3 publications · 81 citations

    3

    h-index

  4. TJ
    Tommi Jaakkola

    Massachusetts Institute of Technology, United States

    3 publications · 81 citations

    3

    h-index

  5. DM
    David M. Upton

    University of Oxford, United Kingdom

    3 publications · 64 citations

    3

    h-index

1–5 of 215

Venues

  1. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 105 citations

    3

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 78 citations

    3

    h-index

  3. ChemRxiv

    Repository · 2 publications · 59 citations

    2

    h-index

  4. BMC Medical Informatics and Decision Making

    1 publications · 19 citations

    1

    h-index

  5. Pattern Recognition

    1 publications · 104 citations

    1

    h-index

1–5