Editors:
- Reports recent research results on Swarm Intelligence in Data Mining
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 34)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
About this book
Swarm Intelligence is an innovative distributed intelligent paradigm for solving optimization problems that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates. Data Mining is an analytic process designed to explore large amounts of data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.
This book deals with the application of swarm intelligence in data mining. Addressing the various issues of swarm intelligence and data mining using different intelligent approaches is the novelty of this edited volume. This volume comprises of 11 chapters including an introductory chapter giving the fundamental definitions and some important research challenges.
Important features include the detailed overview of the various swarm intelligence and data mining paradigms, excellent coverage of timely, advanced data mining topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field. Academics, scientists as well as engineers engaged in research, development and application of optimization techniques and data mining will find the comprehensive coverage of this book invaluable.
Editors and Affiliations
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IITA Professorship Program, School of Computer Science and Engineering Chung-Ang University, Dongjak-gu Seoul, Republic of Korea
Ajith Abraham
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Department of Computer Science, Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj - Napoca, Romania
Crina Grosan
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CVRM-IST, IST, Technical University of Lisbon, Lisboa, Portugal
Vitorino Ramos
Bibliographic Information
Book Title: Swarm Intelligence in Data Mining
Editors: Ajith Abraham, Crina Grosan, Vitorino Ramos
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-34956-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Hardcover ISBN: 978-3-540-34955-6Published: 06 September 2006
Softcover ISBN: 978-3-642-07117-1Published: 30 November 2010
eBook ISBN: 978-3-540-34956-3Published: 12 January 2007
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVIII, 268
Number of Illustrations: 86 b/w illustrations, 5 illustrations in colour
Topics: Theory of Computation, Mathematical and Computational Engineering, Artificial Intelligence