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...
| Other Authors: | Abraham, Ajith, 1968-, Grosan, Crina., Ramos, Vitorino., SpringerLink (Online service) |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Berlin ; New York :
Springer,
2006.
Berlin ; New York : 2006. |
| Physical Description: |
1 online resource (xviii, 267 pages) : 91 figure, 73 table. |
| Series: |
Studies in computational intelligence ;
v. 34. |
| Subjects: |
| Summary: |
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. |
|---|---|
| Item Description: |
Includes bibliographical references and index. Swarm intelligence in data mining / Crina Grosan, Ajith Abraham, and Monica Chis -- Ants constructing rule-based classifiers / David Martens [and others] -- Performing feature selection with ACO / Richard Jensen -- Simultaneous ant colony optimization algorithms for learning linguistic fuzzy rules / Michelle Galea, Qiang Shen -- Ant colony clustering and feature extraction for anomaly intrustion detection / Chi-Ho Tsang, Sam Kwong -- Particle swarm optimization for pattern recognition and image processing / Mahamed G.H. Omran, Andries P. Engelbrecht, Ayed Salman -- Data and text mining with hierarchical clustering ants / Hanene Azzag, Christiane Guinot, Gilles Venturini -- Swarm clustering based on flowers pollination by artificial bees / Majid Kazemian [and others] -- Computer study of the evolution of "news foragers" on the Internet / Zsolt Palotai, Sándor Mandusitz, András Lőrincz. 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. English. Available to OhioLINK libraries. |
| Physical Description: |
1 online resource (xviii, 267 pages) : 91 figure, 73 table. |
| Bibliography: |
Includes bibliographical references and index. |
| ISBN: |
9783540349563 3540349561 3540349553 9783540349556 661074422X 9786610744220 1280744227 9781280744228 |
| ISSN: |
1860-949X ; |
| Access: |
Available to OhioLINK libraries. |