Ebook: Swarm Intelligence in Data Mining

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.

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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.

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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.

Content:
Front Matter....Pages I-XVIII
Swarm Intelligence in Data Mining....Pages 1-20
Ants Constructing Rule-Based Classifiers....Pages 21-43
Performing Feature Selection with ACO....Pages 45-73
Simultaneous Ant Colony Optimization Algorithms for Learning Linguistic Fuzzy Rules....Pages 75-99
Ant Colony Clustering and Feature Extraction for Anomaly Intrusion Detection....Pages 101-123
Particle Swarm Optimization for Pattern Recognition and Image Processing....Pages 125-151
Data and Text Mining with Hierarchical Clustering Ants....Pages 153-189
Swarm Clustering Based on Flowers Pollination by Artificial Bees....Pages 191-202
Computer study of the evolution of ‘news foragers' on the Internet....Pages 203-219
Data Swarm Clustering....Pages 221-241
Clustering Ensemble Using ANT and ART....Pages 243-264
Back Matter....Pages 265-267

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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.

Content:
Front Matter....Pages I-XVIII
Swarm Intelligence in Data Mining....Pages 1-20
Ants Constructing Rule-Based Classifiers....Pages 21-43
Performing Feature Selection with ACO....Pages 45-73
Simultaneous Ant Colony Optimization Algorithms for Learning Linguistic Fuzzy Rules....Pages 75-99
Ant Colony Clustering and Feature Extraction for Anomaly Intrusion Detection....Pages 101-123
Particle Swarm Optimization for Pattern Recognition and Image Processing....Pages 125-151
Data and Text Mining with Hierarchical Clustering Ants....Pages 153-189
Swarm Clustering Based on Flowers Pollination by Artificial Bees....Pages 191-202
Computer study of the evolution of ‘news foragers' on the Internet....Pages 203-219
Data Swarm Clustering....Pages 221-241
Clustering Ensemble Using ANT and ART....Pages 243-264
Back Matter....Pages 265-267
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