Graph clustering has generally concerned itself with clustering undirected graphs; however the graphs from a number of important domains are essentially directed, e.g. networks of...
Abstract. The problem of clustering data can be formulated as a graph partitioning problem. In this setting, spectral methods for obtaining optimal solutions have received a lot of...
Marcus Weber, Wasinee Rungsarityotin, Alexander Sc...
Both document clustering and word clustering are well studied problems. Most existing algorithms cluster documents and words separately but not simultaneously. In this paper we pr...
Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
This paper presents a new partitioning algorithm to perform matrix multiplication on two interconnected heterogeneous processors. Data is partitioned in a way which minimizes the ...