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...
The practical realization of managing and executing large scale scientific computations efficiently and reliably is quite challenging. Scientific computations often invo...
Yong Zhao, Ioan Raicu, Ian T. Foster, Mihael Hateg...
Ubiquitous Knowledge Discovery is a new research area at the intersection of machine learning and data mining with mobile and distributed systems. In this paper the main character...
With rapid technological advances in network infrastructure, programming languages, compatible component interfaces and so many more areas, today the computational Grid has evolve...
ion and abstraction. By the end of the 20th century, technology had advanced to the point where computerized methods had revolutionized surveying and mapmaking practices. Now, the ...