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Constrained clustering
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In computer science, constrained clustering is a class of semi-supervised learning algorithms. Typically, constrained clustering incorporates either…
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Cluster analysis
Computer science
Semi-supervised learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2014
Highly Cited
2014
Internet Traffic Classification Using Constrained Clustering
Yang Wang
,
Yang Xiang
,
Jun Zhang
,
Wanlei Zhou
,
Guiyi Wei
,
L. Yang
IEEE Transactions on Parallel and Distributed…
2014
Corpus ID: 3848105
Statistics-based Internet traffic classification using machine learning techniques has attracted extensive research interest…
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Highly Cited
2013
Highly Cited
2013
Constrained Clustering and Its Application to Face Clustering in Videos
Baoyuan Wu
,
Yifan Zhang
,
Bao-Gang Hu
,
Q. Ji
IEEE Conference on Computer Vision and Pattern…
2013
Corpus ID: 12202856
In this paper, we focus on face clustering in videos. Given the detected faces from real-world videos, we partition all faces…
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Highly Cited
2012
Highly Cited
2012
On constrained spectral clustering and its applications
Xiang Wang
,
B. Qian
,
I. Davidson
Data mining and knowledge discovery
2012
Corpus ID: 316771
Constrained clustering has been well-studied for algorithms such as K-means and hierarchical clustering. However, how to satisfy…
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Review
2011
Review
2011
Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion?
F. Murtagh
,
P. Legendre
Journal of Classification
2011
Corpus ID: 7134583
The Ward error sum of squares hierarchical clustering method has been very widely used since its first description by Ward in a…
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Highly Cited
2010
Highly Cited
2010
Flexible constrained spectral clustering
Xiang Wang
,
I. Davidson
Knowledge Discovery and Data Mining
2010
Corpus ID: 2948946
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how…
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Highly Cited
2008
Highly Cited
2008
Regionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP)
Diansheng Guo
International Journal of Geographical Information…
2008
Corpus ID: 12717830
Regionalization is to divide a large set of spatial objects into a number of spatially contiguous regions while optimizing an…
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Highly Cited
2008
Highly Cited
2008
Constrained spectral clustering through affinity propagation
Zhengdong Lu
,
M. A. Carreira-Perpiñán
IEEE Conference on Computer Vision and Pattern…
2008
Corpus ID: 242900
Pairwise constraints specify whether or not two samples should be in one cluster. Although it has been successful to incorporate…
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Highly Cited
2008
Highly Cited
2008
Non-negative matrix factorization for semi-supervised data clustering
Yanhua Chen
,
M. Rege
,
Ming Dong
,
Jing Hua
Knowledge and Information Systems
2008
Corpus ID: 12157366
Traditional clustering algorithms are inapplicable to many real-world problems where limited knowledge from domain experts is…
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Highly Cited
2004
Highly Cited
2004
Active Semi-Supervision for Pairwise Constrained Clustering
Sugato Basu
,
A. Banerjee
,
R. Mooney
SDM
2004
Corpus ID: 2852345
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a…
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Highly Cited
2000
Highly Cited
2000
Constrained K-Means Clustering
Kristin P. Bennett
,
P. Bradley
,
A. Demiriz
2000
Corpus ID: 16815800
We consider practical methods for adding constraints to the K-Means clustering algorithm in order to avoid local solutions with…
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