Graph Summarization

Graph Summarization is a graph analytics technique that belongs to the class of data reduction methods, specifically distinguished by its focus on generating a compact, lossy representation of a graph that preserves essential structural patterns, node relationships, and domain-specific properties for efficient storage, querying, and analysis.

135

Publications

7.2K

Citations

372

Authors

176

Institutions

Publications per year

2017–2026

54

Authors

372

  1. DK
    Danai Koutra

    University of Michigan, United States

    9 publications · 440 citations

    9

    h-index

  2. CF
    Christos Faloutsos

    Carnegie Mellon University, United States

    8 publications · 580 citations

    8

    h-index

  3. FB
    Francesco Bonchi

    Yahoo (Spain), Spain

    6 publications · 206 citations

    6

    h-index

  4. YW
    Yinghui Wu

    Washington State University, United States

    4 publications · 180 citations

    4

    h-index

  5. AK
    Arijit Khan

    Nanyang Technological University, Singapore

    4 publications · 105 citations

    4

    h-index

1–5 of 372

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 10 publications · 379 citations

    10

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 7 publications · 266 citations

    7

    h-index

  3. HAL (Le Centre pour la Communication Scientifique Directe)

    Repository · 2 publications · 25 citations

    2

    h-index

  4. Information Processing & Management

    2 publications · 156 citations

    2

    h-index

  5. arXiv (Cornell University)

    Repository · 2 publications · 276 citations

    2

    h-index

1–5