In this paper we study asymmetric proximity measures on directed graphs, which quantify the relationships between two nodes or two groups of nodes. The measures are useful in seve...
Heterogeneous data co-clustering has attracted more and more attention in recent years due to its high impact on various applications. While the co-clustering algorithms for two t...
Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, ...
We perform a clustering of the Chilean Web Graph using a local fitness measure, optimized by simulated annealing, and compare the obtained cluster distribution to that of two mod...
One of the challenges in unsupervised machine learning is finding the number of clusters in a dataset. Clustering Validity Indices (CVI) are popular tools used to address this pro...
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...