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ICML
2005
IEEE
16 years 7 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
AAIM
2009
Springer
101views Algorithms» more  AAIM 2009»
16 years 28 days ago
Orca Reduction and ContrAction Graph Clustering
During the last years, a wide range of huge networks has been made available to researchers. The discovery of natural groups, a task called graph clustering, in such datasets is a ...
Daniel Delling, Robert Görke, Christian Schul...
ICPR
2008
IEEE
16 years 23 days ago
A new multiobjective simulated annealing based clustering technique using stability and symmetry
Most clustering algorithms operate by optimizing (either implicitly or explicitly) a single measure of cluster solution quality. Such methods may perform well on some data sets bu...
Sriparna Saha, Sanghamitra Bandyopadhyay
INFOSCALE
2006
ACM
16 years 8 days ago
PENS: an algorithm for density-based clustering in peer-to-peer systems
Huge amounts of data are available in large-scale networks of autonomous data sources dispersed over a wide area. Data mining is an essential technology for obtaining hidden and v...
Mei Li, Guanling Lee, Wang-Chien Lee, Anand Sivasu...
CCGRID
2005
IEEE
15 years 12 months ago
Cluster security with NVisionCC: process monitoring by leveraging emergent properties
We have observed that supercomputing clusters made up of commodity off-the-shelf computers possess emergent properties that are apparent when these systems are considered as an in...
Gregory A. Koenig, Xin Meng, Adam J. Lee, Michael ...