Abstract
In many applications fields, we can obtain benefits from analyzing large distributed data sets by using the high performance computational power. The Grid provides an unrivalled technology for large scale distributed computing as it enables collaboration over the global and the use of distributed computing resources, while also facilitating access to geographically distributed data sets. In this paper, we present a framework for high performance DDM applications in Computational Grid environments called DMGrid, which is based on Grid mechanisms and implemented on top of the Globus 4.0 toolkit.
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Gao, K., Xi, L., Li, J. (2007). A Framework to Support Distributed Data Mining on Grid. In: Castillo, O., Melin, P., Ross, O.M., Sepúlveda Cruz, R., Pedrycz, W., Kacprzyk, J. (eds) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Advances in Soft Computing, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72434-6_48
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DOI: https://doi.org/10.1007/978-3-540-72434-6_48
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