Prototype-based Clustering

Prototype-Based Clustering is a clustering method that partitions documents into groups by representing each cluster with a single prototype—such as a centroid or medoid—which serves as the central exemplar distinguishing it from other clusters based on proximity measures.

109

Publications

9.4K

Citations

299

Authors

149

Institutions

Publications per year

2017–2026

32

Authors

299

  1. WP
    Witold Pedrycz

    University of Alberta, Canada

    7 publications · 425 citations

    7

    h-index

  2. JC
    James C. Bezdek

    University of West Florida, United States

    5 publications · 499 citations

    5

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  3. RJ
    Richard J. Hathaway

    Georgia Southern University, United States

    3 publications · 166 citations

    3

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  4. JJ
    Jinchao Ji

    Northeast Normal University, China

    3 publications · 330 citations

    3

    h-index

  5. BM
    Boris Mirkin

    Birkbeck, University of London, United Kingdom

    2 publications · 133 citations

    2

    h-index

1–5 of 299

Venues

  1. IEEE Transactions on Fuzzy Systems

    TFS · 6 publications · 564 citations

    6

    h-index

  2. Pattern Recognition

    6 publications · 256 citations

    6

    h-index

  3. Pattern Recognition Letters

    4 publications · 170 citations

    4

    h-index

  4. 3

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  5. 3

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1–5