Studies in Computational Intelligence, Volume 34: 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. 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 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. Swarm behavior can be seen in bird flocks, fish schools, as well as in insects like mosquitoes and midges.