Alignment Heuristics

Alignment Heuristics is a computational strategy within network alignment that employs approximate, often greedy, methods to efficiently identify node correspondences across networks by prioritizing local topological or attribute similarities, distinguishing itself from exact or globally optimal approaches through its focus on scalability and practical tractability in large-scale or complex network scenarios.

24

Publications

1.1K

Citations

81

Authors

44

Institutions

Publications per year

2017–2026

3

Authors

81

  1. EA
    Eric A. Hansen

    Mississippi State University, United States

    2 publications · 61 citations

    2

    h-index

  2. MH
    Martin Herbordt

    Boston University, United States

    2 publications · 128 citations

    2

    h-index

  3. GM
    Giovanni Micale

    University of Catania, Italy

    1 publications · 31 citations

    1

    h-index

  4. OK
    Oliver Knodel

    Technische Universität Dresden, Germany

    1 publications · 37 citations

    1

    h-index

  5. JT
    Joshua T Vogelstein

    Johns Hopkins University, United States

    1 publications · 123 citations

    1

    h-index

1–5 of 81

Venues

  1. PLoS ONE

    2 publications · 45 citations

    2

    h-index

  2. Journal of Computer-Aided Molecular Design

    1 publications · 17 citations

    1

    h-index

  3. Technological Forecasting and Social Change

    1 publications · 111 citations

    1

    h-index

  4. 1

    h-index

  5. Business Process Management Journal

    BPMJ · 1 publications · 26 citations

    1

    h-index

1–5