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Advances in Distributed and Parallel Knowledge Discovery (American Association for Artificial Intelligence) - Softcover

 
9780262611558: Advances in Distributed and Parallel Knowledge Discovery (American Association for Artificial Intelligence)

Synopsis

This book presents introductions to DKD and PKD, extensive reviews of the field, and state-of-the-art techniques.

Foreword by Vipin Kumar Knowledge discovery and data mining (KDD) deals with the problem of extracting interesting associations, classifiers, clusters, and other patterns from data. The emergence of network-based distributed computing environments has introduced an important new dimension to this problem―distributed sources of data. Traditional centralized KDD typically requires central aggregation of distributed data, which may not always be feasible because of limited network bandwidth, security concerns, scalability problems, and other practical issues. Distributed knowledge discovery (DKD) works with the merger of communication and computation by analyzing data in a distributed fashion. This technology is particularly useful for large heterogeneous distributed environments such as the Internet, intranets, mobile computing environments, and sensor-networks.When the data sets are large, scaling up the speed of the KDD process is crucial. Parallel knowledge discovery (PKD) techniques addresses this problem by using high-performance multiprocessor machines. This book presents introductions to DKD and PKD, extensive reviews of the field, and state-of-the-art techniques.

Contributors
Rakesh Agrawal, Khaled AlSabti, Stuart Bailey, Philip Chan, David Cheung, Vincent Cho, Joydeep Ghosh, Robert Grossman, Yi-ke Guo, John Hale, John Hall, Daryl Hershberger, Ching-Tien Ho, Erik Johnson, Chris Jones, Chandrika Kamath, Hillol Kargupta, Charles Lo, Balinder Malhi, Ron Musick, Vincent Ng, Byung-Hoon Park, Srinivasan Parthasarathy, Andreas Prodromidis, Foster Provost, Jian Pun, Ashok Ramu, Sanjay Ranka, Mahesh Sreenivas, Salvatore Stolfo, Ramesh Subramonian, Janjao Sutiwaraphun, Kagan Tummer, Andrei Turinsky, Beat Wüthrich, Mohammed Zaki, Joshua Zhang

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About the Author

Hillol Kargupta is Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County.

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Kargupta, H. and Chan, P. (eds)
Published by MIT Press, 2000
ISBN 10: 0262611554 ISBN 13: 9780262611558
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Kargupta, Hillol (editor); Chan, Philip (editor)
Published by MIT Press, Cambridge, MA, 2000
ISBN 10: 0262611554 ISBN 13: 9780262611558
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ISBN 10: 0262611554 ISBN 13: 9780262611558
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