Clustered Partitioning

Clustered Partitioning is a data partitioning method that organizes data into disjoint subsets based on proximity or similarity metrics, such that entities within each subset exhibit higher internal cohesion compared to entities in other subsets.

35

Publications

2.2K

Citations

90

Authors

53

Institutions

Publications per year

2017–2026

9

Authors

90

  1. MJ
    Michael J. Brusco

    Florida State University, United States

    3 publications · 202 citations

    3

    h-index

  2. JC
    James C. Bezdek

    University of West Florida, United States

    3 publications · 388 citations

    3

    h-index

  3. LH
    Lawrence Hall

    University of South Florida, United States

    2 publications · 87 citations

    2

    h-index

  4. DS
    Douglas Steinley

    University of Missouri, United States

    2 publications · 138 citations

    2

    h-index

  5. MP
    Michal Parnas

    Tel Aviv University, Israel

    2 publications · 105 citations

    2

    h-index

1–5 of 90

Venues

  1. Psychometrika

    2 publications · 144 citations

    2

    h-index

  2. Psychological Methods

    2 publications · 127 citations

    2

    h-index

  3. Pattern Recognition

    1 publications · 16 citations

    1

    h-index

  4. Journal of Imaging

    1 publications · 16 citations

    1

    h-index

  5. Biometrics

    1 publications · 57 citations

    1

    h-index

1–5