Aggregation-based Visualization

Aggregation-Based Visualization is a multilevel graph visualization technique that synthesizes complex graph structures into simplified, hierarchical representations by grouping nodes and edges into higher-level aggregates based on structural or semantic criteria, enabling scalable exploration of large-scale networks.

41

Publications

4.9K

Citations

131

Authors

81

Institutions

Publications per year

2017–2026

11

Authors

131

  1. BS
    Ben Shneiderman

    University of Maryland, College Park, United States

    2 publications · 274 citations

    2

    h-index

  2. RS
    Robert Susmaga

    Poznań University of Technology, Poland

    2 publications · 46 citations

    2

    h-index

  3. AT
    Andrew Tomkins

    IBM Research - Almaden, United States

    2 publications · 302 citations

    2

    h-index

  4. QL
    Qi Liao

    Central Michigan University, United States

    2 publications · 39 citations

    2

    h-index

  5. GH
    Gregor Hackenbroich

    University of Duisburg-Essen, Germany

    2 publications · 128 citations

    2

    h-index

1–5 of 131

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 8 publications · 3.4K citations

    8

    h-index

  2. Information Sciences

    2 publications · 109 citations

    2

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 169 citations

    2

    h-index

  4. Applied Ergonomics

    1 publications · 21 citations

    1

    h-index

  5. ACM Transactions on the Web

    TWEB · 1 publications · 88 citations

    1

    h-index

1–5