Semi-supervised Clustering
Semi-Supervised Clustering is a clustering method that incorporates limited supervision, typically in the form of pairwise constraints or labeled examples, to guide the formation of clusters in otherwise unsupervised data.
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29.6K
Citations
2.1K
Authors
758
Institutions
Publications per year
2017–2026
283
605
A probabilistic framework for semi-supervised clustering
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney · 2004 · 819 citations
Hans‐Peter Kriegel, Peer Kröger, Jörg Sander et al. · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · 2011 · 810 citations
Semi-supervised Clustering by Seeding
Sugato Basu, Arindam Banerjee, Raymond J. Mooney · 2002 · 806 citations
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758

City University of Hong Kong
Hong Kong, Hong Kong
15 h-index
43 publications
2.1K citations

Chinese Academy of Sciences
Beijing, China
13 h-index
32 publications
1.5K citations

Xidian University
Xi'an, China
12 h-index
37 publications
1.8K citations
Nanyang Technological University
Singapore, Singapore
12 h-index
21 publications
1.2K citations
Guangdong University of Technology
Guangzhou, China
12 h-index
36 publications
1.4K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
11 h-index
14 publications
993 citations
The University of Texas at Austin
Austin, United States
11 h-index
26 publications
9.1K citations

Northwestern Polytechnical University
Xi'an, China
11 h-index
24 publications
3K citations
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TKDE · 20 publications · 1.2K citations
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14 publications · 795 citations
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12 publications · 822 citations
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14 publications · 479 citations
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13 publications · 573 citations
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