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169
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
166
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ICDM
2009
IEEE
16 years 1 months ago
2009
IEEE
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
185
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SDM
2007
SIAM
15 years 8 months ago
2007
SIAM
In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
218
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AUSAI
2009
Springer
16 years 1 months ago
2009
Springer
In the era of information explosion, structured data emerge on a large scale. As a description of structured data, network has drawn attention of researchers in many subjects. Netw...
195
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SDM
2004
SIAM
15 years 8 months ago
2004
SIAM
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...