Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
We present a framework for an automated generation of exact search tree algorithms for NP-hard problems. The purpose of our approach is two-fold--rapid development and improved up...
A promising approach to graph clustering is based on the intuitive notion of intra-cluster density vs. inter-cluster sparsity. While both formalizations and algorithms focusing on ...
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
In this paper, the effect of the dimensionality of data sets on the exploitation of synergy among known nearest neighbor (NN) editing and condensing tools is analyzed using a synt...