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» Experiments on Graph Clustering Algorithms
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AAIM
2009
Springer
101views Algorithms» more  AAIM 2009»
14 years 2 months 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...
ICML
2009
IEEE
14 years 8 months ago
Spectral clustering based on the graph p-Laplacian
We present a generalized version of spectral clustering using the graph p-Laplacian, a nonlinear generalization of the standard graph Laplacian. We show that the second eigenvecto...
Matthias Hein, Thomas Bühler
INCDM
2010
Springer
172views Data Mining» more  INCDM 2010»
13 years 6 months ago
Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
Many real world systems can be modeled as networks or graphs. Clustering algorithms that help us to organize and understand these networks are usually referred to as, graph based c...
Faraz Zaidi, Daniel Archambault, Guy Melanç...
EDBT
2012
ACM
228views Database» more  EDBT 2012»
11 years 10 months ago
Finding maximal k-edge-connected subgraphs from a large graph
In this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and findin...
Rui Zhou, Chengfei Liu, Jeffrey Xu Yu, Weifa Liang...
PAMI
2007
202views more  PAMI 2007»
13 years 7 months ago
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis