Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
We study a novel clustering problem in which the pairwise relations between objects are categorical. This problem can be viewed as clustering the vertices of a graph whose edges a...
Francesco Bonchi, Aristides Gionis, Francesco Gull...
Subspace clustering has attracted great attention due to its capability of finding salient patterns in high dimensional data. Order preserving subspace clusters have been proven to...
The recent proliferation of graph data in a wide spectrum of applications has led to an increasing demand for advanced data analysis techniques. In view of this, many graph mining ...