Attributed Graph Mining

Attributed Graph Mining is a subfield of graph mining that focuses on extracting patterns, relationships, and knowledge from graphs whose vertices and/or edges are associated with attribute data, thereby enabling richer analysis by integrating structural and attribute information.

58

Publications

3.4K

Citations

186

Authors

98

Institutions

Publications per year

2017–2026

30

Authors

186

  1. PI
    Patricia Iglesias Sánchez

    Karlsruhe Institute of Technology, Germany

    4 publications · 402 citations

    4

    h-index

  2. EM
    Emmanuel Müller

    Karlsruhe Institute of Technology, Germany

    4 publications · 402 citations

    4

    h-index

  3. QZ
    Quanshi Zhang

    Shanghai Jiao Tong University, China

    3 publications · 51 citations

    3

    h-index

  4. MA
    Martin Atzmueller

    University of Kassel, Germany

    3 publications · 51 citations

    3

    h-index

  5. KB
    Klemens Böhm

    Karlsruhe Institute of Technology, Germany

    3 publications · 169 citations

    3

    h-index

1–5 of 186

Venues

  1. Expert Systems with Applications

    3 publications · 87 citations

    3

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 73 citations

    3

    h-index

  3. Neurocomputing

    2 publications · 27 citations

    2

    h-index

  4. Knowledge-Based Systems

    2 publications · 57 citations

    2

    h-index

  5. Knowledge and Information Systems

    2 publications · 34 citations

    2

    h-index

1–5