As an important technique for data analysis, clustering has been employed in many applications such as image segmentation, document clustering and vector quantization. Divisive cl...
Abstract. Several actions are usually performed when document is appended to textual database in information retrieval system. The most frequent actions are compression of the docu...
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
Abstract—Large-scale parallel applications often produce immense quantities of data that need to be analyzed. To avoid performing repeated, costly disk accesses, analysis of larg...
: With the ever-increasing demands on server applications, reliability is of paramount importance. Often these services are implemented using a distributed server cluster architect...