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Based around eleven international real life case studies and including contributions from leading experts in the field this groundbreaking book explores the need for the grid-enabling of data mining applications and provides a comprehensive study of the technology, techniques and management skills necessary to create them. This book provides a simultaneous design blueprint, user guide, and research agenda for current and future developments and will appeal to a broad audience; from developers and users of data mining and grid technology, to advanced undergraduate and postgraduate students interested in this field.

 

Aus dem Inhalt

Preface.

 

List of contributors.

 

1. Data mining meets grid computing: time to dance (Alberto Sánchez, Jesús Montes, Werner Dubitzky, Julio J. Valdés, María S. Pérez and Pedro de Miguel).

 

2. Data analysis services in the Knowledge Grid (Eugenio Cesario, Antonio Congiusta, Domenico Talia and Paolo Trunfio).

 

3. GridMiner: an advanced support for e-science analytics (Peter Brezany, Ivan Janciak and A. Min Tjoa).

 

4. ADaM services: scientific data mining in the service-oriented architecture paradigm (Rahul Ramachandran, Sara Graves, John Rushing, Ken Keiser, Manil Maskey, Hong Lin and Helen Conover).

 

5. Mining for misconfigured machines in grid systems (Noam Palatin, Arie Leizarowitz, Assaf Schuster and Ran Wolff).

 

6. FAEHIM: Federated Analysis Environment for Heterogeneous Intelligent Mining (Ali Shaikh Ali and Omer F. Rana).

 

7. Scalable and privacy preserving distributed data analysis over a service-oriented platform (William K. Cheung).

 

8. Building and using analytical workflows in Discovery Net (Moustafa Ghanem, Vasa Curcin, Patrick Wendel and Yike Guo).

 

9. Building workflows that traverse the bioinformatics data landscape (Robert Stevens, Paul Fisher, Jun Zhao, Carole Goble and Andy Brass).

 

10. Specification of distributed data mining workflows with DataMiningGrid (Dennis Wegener and Michael May).

 

11. Anteater: service-oriented data mining (Renato A. Ferreira, Dorgival O. Guedes and Wagner Meira).

 

12. DMGA: a generic brokering-based data mining grid architecture (Alberto Sánchez, María S. Pérez, Pierre Gueant, José M. Peña and Pilar Herrero).

 

13. Grid-based data mining with the Environmental Scenario Search Engine (ESSE) (Mikhail Zhizhin, Alexey Poyda, Dmitry Mishin, Dmitry Medvedev, Eric Kihn and Vassily Lyutsarev).

 

14. Data pre-processing using OGSA-DAI (Martin Swain and Neil P. Chue Hong).

 

Index.