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WSRF services for learning classifiers from Data Grid

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2 Author(s)
Ben Haj Hmida, M. ; Dept. of Comput. Sci., Fac. of Sci. of Tunisia, Tunis ; Slimani, Y.

In this paper, we present the Weka4GML architecture, a new framework based on WSRF technology for developing meta-learning methods to deal with datasets distributed among data grid. This framework extends the Weka toolkit to support distributed execution of data mining methods, like meta-learning. The architecture and the behavior of the proposed framework are described in this paper. We also detail the different steps needed to execute a meta-learning process on a Globus environment.

Published in:

Computer Systems and Applications, 2009. AICCSA 2009. IEEE/ACS International Conference on

Date of Conference:

10-13 May 2009