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
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9.4K
Citations
299
Authors
149
Institutions
Publications per year
2017–2026
32
Parents
109
Clustering of the self-organizing map
Juha Vesanto, Esa Alhoniemi · IEEE Transactions on Neural Networks · 2000 · 2.7K citations
A probabilistic framework for semi-supervised clustering
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney · 2004 · 819 citations
An efficient k-means clustering algorithm
Khaled Alsabti, Sanjay Ranka, Vineet Kumar Singh · 1997 · 494 citations · Full text
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149

University of Alberta
Edmonton, Canada
8 h-index
9 publications
688 citations

Xidian University
Xi'an, China
5 h-index
18 publications
427 citations
Jilin University
Changchun, China
4 h-index
19 publications
1.7K citations

King Abdulaziz University
Jeddah, Saudi Arabia
4 h-index
4 publications
105 citations
Systems Research Institute
Warsaw, Poland
4 h-index
4 publications
310 citations

Polish Academy of Sciences
Warsaw, Poland
4 h-index
4 publications
311 citations
Nanyang Technological University
Singapore, Singapore
4 h-index
7 publications
314 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
9 publications
653 citations
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TFS · 6 publications · 564 citations
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6 publications · 256 citations
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4 publications · 170 citations
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3 publications · 72 citations
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3 publications · 547 citations
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