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Data Mining in Grid Computing Environments

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.

Rahul Ramachandran, Sara Graves, John Rushing, Ken Keizer, Manil Maskey,
Hong Lin and Helen Conover ABSTRACT The Algorithm Development and
Mining System (ADaM) was originally developed in the early 1990s with the goal
of ...