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Computational Intelligence in Data Mining - Volume 1

Proceedings of the International Conference on CIDM, 20-21 December 2014

  • Lakhmi C. Jain
  • Himansu Sekhar Behera
  • Jyotsna Kumar Mandal
  • Durga Prasad Mohapatra

Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 31)

Table of contents

  1. Jagruti Shah, L. G. Malik
    Pages 563-572
  2. Manoj Kumar Sahoo, Kaliprasanna Swain, Amiya Kumar Rath
    Pages 603-612
  3. Madhusmita Sahu, Swatee Rekha Mohanty, Durga Prasad Mohapatra
    Pages 625-635
  4. Vijaylakshmi Sajwan, Puneet Goyal
    Pages 637-646
  5. K. K. Sahu, G. R. Biswal, P. K. Sahu, S. R. Sahu, H. S. Behera
    Pages 647-664
  6. Tulasichandra Sekhar Gorripotu, Rabindra Kumar Sahu, Sidhartha Panda
    Pages 677-687
  7. Ratnakirti Roy, Suvamoy Changder
    Pages 699-709
  8. Back Matter
    Pages 711-713

About these proceedings

Introduction

The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Keywords

Advance Computing Methods Big Data Analysis CIDM CIDM 2014 CIDM Proceedings Computational Intelligence Data Mining Fuzzy Logic Systems Machine Learning

Editors and affiliations

  • Lakhmi C. Jain
    • 1
  • Himansu Sekhar Behera
    • 2
  • Jyotsna Kumar Mandal
    • 3
  • Durga Prasad Mohapatra
    • 4
  1. 1.University of Canberra, Canberra, Australia and University of South AustraliaAdelaideAustralia
  2. 2.Department of Computer Science and EngineeringVeer Surendra Sai University of TechnologySambalpurIndia
  3. 3.Computer Science & EngineeringKalyani UniversityNadiaIndia
  4. 4.Dept. of Computer Science and EngineeringNational Institute of Technology RourkelaRourkelaIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-81-322-2205-7
  • Copyright Information Springer India 2015
  • Publisher Name Springer, New Delhi
  • eBook Packages Engineering
  • Print ISBN 978-81-322-2204-0
  • Online ISBN 978-81-322-2205-7
  • Series Print ISSN 2190-3018
  • Series Online ISSN 2190-3026
  • Buy this book on publisher's site