Divisive Clustering

Divisive Clustering is a hierarchical clustering method that belongs to the class of clustering algorithms, distinguished by its top-down approach of recursively partitioning a single cohesive document set into smaller, disjoint clusters until a stopping criterion is met.

209

Publications

34K

Citations

540

Authors

275

Institutions

Publications per year

2017–2026

49

Variants

Top-down ClusteringTop-down Hierarchical Clustering

Authors

540

  1. TX
    Tengke Xiong

    Université de Sherbrooke, Canada

    5 publications · 149 citations

    5

    h-index

  2. SW
    Shengrui Wang

    Université de Sherbrooke, Canada

    5 publications · 149 citations

    5

    h-index

  3. IS
    Inderjit S. Dhillon

    The University of Texas at Austin, United States

    4 publications · 727 citations

    4

    h-index

  4. LM
    Leonard McMillan

    University of North Carolina at Chapel Hill, United States

    3 publications · 135 citations

    3

    h-index

  5. JZ
    Jingdan Zhang

    Siemens (United States), United States

    3 publications · 135 citations

    3

    h-index

1–5 of 540

Venues

  1. Pattern Recognition

    4 publications · 161 citations

    4

    h-index

  2. BMC Bioinformatics

    4 publications · 84 citations

    4

    h-index

  3. Journal of Classification

    4 publications · 381 citations

    4

    h-index

  4. Journal of Vegetation Science

    JVS · 3 publications · 509 citations

    3

    h-index

  5. IEEE Access

    3 publications · 47 citations

    3

    h-index

1–5