Search
 
Home| Join Our Mailing List| New Reviews| New Titles
Editor's Choice| Bestsellers| Textbooks| Book Series| Study Guides| E-Catalogues
  COMPUTER SCIENCE
  Artificial Intelligence
Database/ Information
Sciences

Decision Sciences
Digital Security
Fuzzy Logic
Machine Vision/ Pattern
Recognition

Neural Networks/ Networking
Parallel Processing/
Supercomputing

Software Engineering
Theoretical Computer Science
General
New Titles
August Bestsellers
Editor's Choice
Nobel Lectures
Textbooks
Recent Reviews
Book Series
Related Journals
  • International Journal of Semantic Computing (IJSC)
  • International Journal of Information Acquisition (IJIA)
  • Journal of Information & Knowledge Management (JIKM)
  • Computer Science Journals
  • New Mathematics and Natural Computation (NMNC)
  • Request for related catalogues
     
      PRODUCTS
      Journals
    eBooks
    Journals Archives
    eProceedings
     
      RESOURCES
      For Librarians
    For Authors
    For Booksellers
    For Translation Rights About Us
    Contact Us
    How to Order News
    Inspection Copy
     

    KNOWLEDGE MINING USING INTELLIGENT AGENTS

    edited by Satchidananda Dehuri (Fakir Mohan University, India) & Sung-Bae Cho (Yonsei University, Korea)

    Knowledge Mining Using Intelligent Agents explores the concept of knowledge discovery processes and enhances decision-making capability through the use of intelligent agents like ants, termites and honey bees. In order to provide readers with an integrated set of concepts and techniques for understanding knowledge discovery and its practical utility, this book blends two distinct disciplines — data mining and knowledge discovery process, and intelligent agents-based computing (swarm intelligence and computational intelligence). For the more advanced reader, researchers, and decision/policy-makers are given an insight into emerging technologies and their possible hybridization, which can be used for activities like dredging, capturing, distributions and the utilization of knowledge in their domain of interest (i.e. business, policy-making, etc.).

    By studying the behavior of swarm intelligence, this book aims to integrate the computational intelligence paradigm and intelligent distributed agents architecture to optimize various engineering problems and efficiently represent knowledge from the large gamut of data.

     
    Contents:
    • Part I:
      • Theoretical Foundations of Knowledge Discovery in Databases and DM
      • Theoretical Foundations of Computational Intelligence
      • Theoretical Advances of Swarm Intelligence
    • Part II:
      • Computational Intelligence for Knowledge Discovery
      • Genetic Algorithm for Knowledge Discovery
      • Genetic Programming for Knowledge Discovery
      • Neural Network for Knowledge discovery
      • Multi-objective Evolutionary Algorithms for Knowledge Discovery
      • Fuzzy Approach for Rule/Knowledge Mining
    • Part III:
      • Swarm Intelligence for Knowledge Discovery
      • Particle Swarm Optimization for Knowledge Discovery
      • Ant Colony Optimization for Knowledge Discovery
      • Honey Bee Agents for Knowledge Discovery
      • Termites for Knowledge Discovery
      • Wasps for Rule/Knowledge Mining
    • Part IV:
      • Hybrid Intelligent Agents Techniques for KDD and DM
      • Rough-Fuzzy Granule
      • Neuro-Fuzzy
      • Evolving Neural Network
      • Hybrid Swarm Intelligence
    • Part V:
      • Applications and Future Directions
      • Bio-informatics
      • Computational Financial
      • Marketing/Business
      • Engineering Sciences
     
    Readership: Researchers and professionals in the knowledge discovery industry.
     


     
    400pp (approx.)    Pub. date: Scheduled Fall 2010  
    ISBN:   978-1-84816-386-7
    1-84816-386-X
       US$98 / £74

     


     

    Imperial College Press  |  Global Publishing  |  Asia-Pacific Biotech News  |  Innovation Magazine
    Labcreations Co  |  Meeting Matters  |  National Academies Press

    Copyright © 2009 World Scientific Publishing Co. All rights reserved.
    Updated on 20 November 2009