Swarm Intelligence for Multi-objective Problems in Data Mining

  • Carlos Artemio Coello Coello
  • Satchidananda Dehuri
  • Susmita Ghosh

Part of the Studies in Computational Intelligence book series (SCI, volume 242)

Table of contents

  1. Front Matter
  2. Satchidananda Dehuri, Susmita Ghosh, Carlos A. Coello Coello
    Pages 1-17
  3. Susana M. Vieira, João M. C. Sousa, Thomas A. Runkler
    Pages 19-36
  4. Augusto de Almeida Prado G. Torácio
    Pages 37-64
  5. Seyed-Hamid Zahiri, Seyed-Alireza Seyedin
    Pages 65-92
  6. Satchidananda Dehuri, Carlos A. Coello Coello, Sung-Bae Cho, Ashish Ghosh
    Pages 115-155
  7. André B. de Carvalho, Aurora Pozo
    Pages 179-198
  8. Magnus Lie Hetland
    Pages 199-232
  9. Angel Muñoz-Zavala, Arturo Hernández-Aguirre, Enrique Villa-Diharce
    Pages 233-257
  10. Lisa Osadciw, Nisha Srinivas, Kalyan Veeramachaneni
    Pages 259-281
  11. Back Matter

About this book

Introduction

The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining. Such a collection intends to illustrate the potential of multi-objective swarm intelligence techniques in data mining, with the aim of motivating more researchers in evolutionary computation and machine learning to do research in this field.

This volume consists of eleven chapters, including an introduction that provides the basic concepts of swarm intelligence techniques and a discussion of their use in data mining. Some of the research challenges that must be faced when using swarm intelligence techniques in data mining are also addressed. The rest of the chapters were contributed by leading researchers, and were organized according to the steps normally followed in Knowledge Discovery in Databases (KDD) (i.e., data preprocessing, data mining, and post processing).

We hope that this book becomes a valuable reference for those wishing to do research on the use of multi-objective swarm intelligence techniques in data mining and knowledge discovery in databases.

Keywords

algorithms classification data mining decision tree evolution evolutionary computation intelligence knowledge knowledge discovery learning machine learning multi-objective optimization neural networks optimization swarm intelligence

Editors and affiliations

  • Carlos Artemio Coello Coello
    • 1
  • Satchidananda Dehuri
    • 2
  • Susmita Ghosh
    • 3
  1. 1.Departamento de ComputacionCINVESTAV-IPNMexico07360
  2. 2.Department of information and Communication TechnologyFakirMohan UniversityBalasoreIndia
  3. 3.Department of Computer Science and EngineeringJadavpur UniversityKolkataIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-03625-5
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-03624-8
  • Online ISBN 978-3-642-03625-5
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book