Abstract— We describe a grid-based approach for enterprisescale data mining that leverages database technology for I/O parallelism, and on-demand compute servers for compute para...
The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Distributed Data Mining (DDM), calls for the support of a powerful Grid with an e...
Data privacy is a major concern that threatens the widespread deployment of Data Grids in domains such as health-care and finance. We propose a unique approach for obtaining knowl...
Abstract. Recently we presented a new approach [5, 6] to the classification problem arising in data mining. It is based on the regularization network approach, but in contrast to ...
In parallel computing environments such as HPC clusters and the Grid, data-intensive applications involve large overhead costs due to a concentration of access to the files on co...