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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. D. K. Behera, P. K. Patra
    Pages 233-242
  2. Rupashree Sethi, Sidhartha Panda, Bibhuti Prasad Sahoo
    Pages 251-263
  3. Shashikumar G. Totad, A. Smitha Kranthi, A. K. Matta
    Pages 285-292
  4. Bharat Rochani, Rajesh Kumar Raj, Sanjay Gurjar, M. SantoshKumar Singh
    Pages 293-302
  5. Bishwa Ranjan Das, Srikanta Patnaik, Sarada Baboo, Niladri Sekhar Dash
    Pages 315-324
  6. D. P. Kanungo, Bighnaraj Naik, Janmenjoy Nayak, Sarada Baboo, H. S. Behera
    Pages 333-344
  7. S. Swapna Kumar, S. Vishwas
    Pages 345-354
  8. K. J. Latesh Kumar, R. Lawrance
    Pages 365-373
  9. Nesdi Evrilyan Rozanda, M. Ismail, Inggih Permana
    Pages 375-386
  10. Deepa S. Deshpande, Archana M. Rajurkar, Ramchandra R. Manthalkar
    Pages 387-400
  11. Janmenjoy Nayak, Bighnaraj Naik, H. S. Behera, Ajith Abraham
    Pages 401-414
  12. Terence Johnson, Santosh Kumar Singh
    Pages 415-425

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