From Parallel Data Mining to Grid-Enabled Distributed Knowledge Discovery

Author:

Cesario Eugenio,Talia Domenico

Publisher

Springer Berlin Heidelberg

Reference15 articles.

1. Cohen, W.W.: Fast Effective Rule Induction. In: Proc. of the 12th Int. Conf. Machine Learning (ICML’95), Tahoe City, California, USA, pp. 115–123 (1995)

2. Provost, F.J., Aronis, J.M.: Scaling up inductive learning with massive parallelism. International Journal of Machine Learning 23(1), 33–46 (1996)

3. Skillicorn, D.: Strategies for Parallel Data Mining. IEEE Concurrency 7(4), 26–35 (1999)

4. Lecture Notes in Computer Science;D. Talia,2002

5. Foster, I., et al.: The Physiology of the Grid: An Open Grid Services Architecture for Distributed Systems Integration. Globus Project (2002), http://www.globus.org/alliance/publications/papers/ogsa.pdf

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