Community Pattern Discovery

Community Pattern Discovery is a methodological framework within community visualization that identifies and characterizes recurrent structural and behavioral motifs in community-organized data by integrating computational detection techniques with interpretative visual analytics to reveal meaningful, latent patterns in social or networked entities.

41

Publications

2.9K

Citations

134

Authors

81

Institutions

Publications per year

2017–2026

12

Authors

134

  1. MA
    Martin Atzmueller

    University of Kassel, Germany

    4 publications · 102 citations

    4

    h-index

  2. LT
    Lei Tang

    Arizona State University, United States

    2 publications · 189 citations

    2

    h-index

  3. SL
    Ser-Nam Lim

    University of Maryland, College Park, United States

    2 publications · 98 citations

    2

    h-index

  4. NK
    Nils Krahnstoever

    GE Global Research (United States), United States

    2 publications · 98 citations

    2

    h-index

  5. FP
    Fabio Palomba

    University of Salerno, Italy

    2 publications · 94 citations

    2

    h-index

1–5 of 134

Venues

  1. 2

    h-index

  2. Ecological Modelling

    2 publications · 387 citations

    2

    h-index

  3. 2

    h-index

  4. 2009 IEEE Conference on Computer Vision and Pattern Recognition

    Conference · 2 publications · 98 citations

    2

    h-index

  5. Food Quality and Preference

    1 publications · 34 citations

    1

    h-index

1–5