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. Front Matter
    Pages i-xxviii
  2. Hardeep Singh Kang, Kulwinder Singh Mann
    Pages 1-9
  3. Sumit Kumar Pandey, Vijaya Laxmi
    Pages 11-21
  4. Tirtharaj Dash, Sanjib Kumar Nayak, H. S. Behera
    Pages 35-43
  5. N. K. S. Behera, M. K. Sahoo, H. S. Behera
    Pages 45-56
  6. S. R. Sahu, D. P. Kanungo, H. S. Behera
    Pages 57-65
  7. Maroti Deshmukh, Munaga V. N. K. Prasad
    Pages 77-86
  8. Mohammed Abdul Khaleel, G. N. Dash, K. S. Choudhury, Mohiuddin Ali Khan
    Pages 87-96
  9. Prashant Kumar, Rahul Pukale
    Pages 109-121
  10. Satishkumar Varma, Sanjay Talbar
    Pages 123-130
  11. Ajay Rawat, Rama Sushil, Lalit Sharm
    Pages 131-141
  12. Charulata Palai, Pradeep Kumar Jena
    Pages 143-153
  13. Y. L. Malathi Latha, Munaga V. N. K. Prasad
    Pages 155-163
  14. Mattupalli Komal Teja, Sajja Karthik, Kommu Lavanya Kumari, Kothuri Sriraman
    Pages 165-174
  15. Ashis Behera, Madhumita Panda
    Pages 175-186
  16. Rama Seshagiri Rao Channapragada, Munaga V. N. K. Prasad
    Pages 199-211

About these proceedings


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.


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
  • 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
  • About this book