Distributed Data Mining: Implementing Data Mining Jobs on Grid Environments

Author(s):  
Vishal Bhemwala ◽  
Bhavesh Patel ◽  
Ashok Patel

Data mining technology is not only composed by efficient and effective algorithms, executed as standalone kernels. Rather, it is constituted by complex applications articulated in the non-trivial interaction among hardware and software components, running on large scale distributed environments. This last feature turns out to be both the cause and the effect of the inherently distributed nature of data, on one side, and, on the other side, of the spatiotemporal complexity that characterizes many DM applications. For a growing number of application fields, Distributed Data Mining (DDM) is therefore a critical technology. In this research paper, after reviewing the open problems in DDM, we describe the DM jobs on Grid environments. We will introduce the design of Knowledge Grid System.

2011 ◽  
Vol 268-270 ◽  
pp. 1000-1000

Removed due to plagiarism.The original paper was published as: S. Saberi, P. Trunfio, D. Talia, M. Fesharaki, K. Badie, "Using Social Network and Semantic Overlay Network Approaches to Share Knowledge in Distributed Data Mining Scenarios". Proc. of the 8th Int. Conference on High Performance Computing and Simulation (HPCS 2010), Caen, France, pp. 536-544, IEEE Computer Society Press, June 2010. ISBN 978-1-4244-6827-0. DOI: 10.1109/HPCS.2010.5547080


2017 ◽  
Vol 93 ◽  
pp. 23-30 ◽  
Author(s):  
Xavier Limón ◽  
Alejandro Guerra-Hernández ◽  
Nicandro Cruz-Ramírez ◽  
Héctor-Gabriel Acosta-Mesa ◽  
Francisco Grimaldo

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