Swarm Intelligence in Data Mining (Studies in Computational Intelligence, 34)

ISBN 10: 3540349553 / ISBN 13: 9783540349556

Verlag: Springer, 2006

Beschreibung

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Bestandsnummer des Verkäufers Z1-C-014-02230

Bibliografische Details

• Titel: Swarm Intelligence in Data Mining (Studies in Computational Intelligence, 34)
• Verlag: Springer
• Veröffentlichungsdatum: 2006
• Sprache: Englisch
• ISBN-10: 3540349553
• ISBN-13: 9783540349556
• Bindung: Hardcover
• Zustand: Good

Über diesen Titel

Inhaltsangabe

This volume examines the application of swarm intelligence in data mining, addressing the issues of swarm intelligence and data mining using novel intelligent approaches. The book comprises 11 chapters including an introduction reviewing fundamental definitions and important research challenges. Important features include a detailed overview of swarm intelligence and data mining paradigms, focused coverage of timely, advanced data mining topics, state-of-the-art theoretical research and application developments and contributions by pioneers in the field.

Von der hinteren Coverseite

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.