The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
This paper describes work in progress to develop a standard for interoperability among high-performance scientific components. This research stems from growing recognition that th...
Robert C. Armstrong, Dennis Gannon, Al Geist, Kata...
Multidimensional Analysis in On-Line Analytical Processing (OLAP), and Scientific and statistical databases (SSDB) use operations requiring summary information on multi-dimensiona...
—In this paper, we present an effective and scalable system for multivariate volume data visualization and analysis with a novel transfer function interface design that tightly c...
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...