Amazon cover image
Image from Amazon.com

Swarm Intelligence in Data Mining [electronic resource] / edited by Ajith Abraham, Crina Grosan, Vitorino Ramos.

By: Contributor(s): Material type: TextTextSeries: Studies in Computational Intelligence ; 34Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Description: XVIII, 268 p. 91 illus., 5 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540349563
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 519 23
LOC classification:
  • TA329-348
  • TA640-643
Online resources:
Contents:
Swarm Intelligence in Data Mining -- Ants Constructing Rule-Based Classifiers -- Performing Feature Selection with ACO -- Simultaneous Ant Colony Optimization Algorithms for Learning Linguistic Fuzzy Rules -- Ant Colony Clustering and Feature Extraction for Anomaly Intrusion Detection -- Particle Swarm Optimization for Pattern Recognition and Image Processing -- Data and Text Mining with Hierarchical Clustering Ants -- Swarm Clustering Based on Flowers Pollination by Artificial Bees -- Computer study of the evolution of ‘news foragers' on the Internet -- Data Swarm Clustering -- Clustering Ensemble Using ANT and ART.
In: Springer eBooksSummary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Status Date due Barcode
E-Book E-Book Central Library Available E-43418

Swarm Intelligence in Data Mining -- Ants Constructing Rule-Based Classifiers -- Performing Feature Selection with ACO -- Simultaneous Ant Colony Optimization Algorithms for Learning Linguistic Fuzzy Rules -- Ant Colony Clustering and Feature Extraction for Anomaly Intrusion Detection -- Particle Swarm Optimization for Pattern Recognition and Image Processing -- Data and Text Mining with Hierarchical Clustering Ants -- Swarm Clustering Based on Flowers Pollination by Artificial Bees -- Computer study of the evolution of ‘news foragers' on the Internet -- Data Swarm Clustering -- Clustering Ensemble Using ANT and ART.

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.

There are no comments on this title.

to post a comment.

Maintained by VTU Library