Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
—As parallel file systems span larger and larger numbers of nodes in order to provide the performance and scalability necessary for modern cluster applications, the need for fau...
Biclustering refers to simultaneous clustering of objects and their features. Use of biclustering is gaining momentum in areas such as text mining, gene expression analysis and co...
Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-...
A digital library system consists of LVS(Linux Virtual Server) operating with software clustering technology provides is designed on Linux environment. In the cluster of servers fa...