Evolutionary Clustering

Evolutionary Clustering is a computational framework within evolutionary computation that dynamically groups data instances into clusters over time by iteratively applying evolutionary operators such as selection, mutation, and recombination to optimize cluster quality and adapt to changes in data distribution.

346

Publications

16.3K

Citations

907

Authors

450

Institutions

Publications per year

2017–2026

104

Authors

907

  1. LJ
    Licheng Jiao

    Xidian University, China

    8 publications · 270 citations

    8

    h-index

  2. ER
    Eduardo R. Hruschka

    Universidade de São Paulo, Brazil

    8 publications · 1.2K citations

    8

    h-index

  3. RJ
    Ricardo J. G. B. Campello

    Universidade de São Paulo, Brazil

    7 publications · 977 citations

    7

    h-index

  4. CP
    Clara Pizzuti

    Institute for High Performance Computing and Networking, Italy

    7 publications · 523 citations

    7

    h-index

  5. MG
    Maoguo Gong

    Xidian University, China

    6 publications · 172 citations

    6

    h-index

1–5 of 907

Venues

  1. Expert Systems with Applications

    9 publications · 352 citations

    9

    h-index

  2. Knowledge-Based Systems

    6 publications · 154 citations

    7

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 6 publications · 681 citations

    6

    h-index

  4. IEEE Transactions on Evolutionary Computation

    6 publications · 1.3K citations

    6

    h-index

  5. Soft Computing

    5 publications · 163 citations

    5

    h-index

1–5