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Computational Intelligence in Data Mining - Volume 3 : Proceedings of the International Conference on CIDM, 20-21 December 2014

Author: Lakhmi C Jain; Himansu Sekhar Behera; Jyotsna Kumar Mandal; Durga Prasad Mohapatra
Publisher: New Delhi : Springer, 2015.
Series: Smart Innovation, Systems and Technologies ; 33; SpringerLink : Bücher
Edition/Format:   eBook : EnglishView all editions and formats
Summary:
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  Read more...
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Material Type: Internet resource
Document Type: Internet Resource
All Authors / Contributors: Lakhmi C Jain; Himansu Sekhar Behera; Jyotsna Kumar Mandal; Durga Prasad Mohapatra
ISBN: 9788132222026 8132222024
OCLC Number: 903305778
Description: Online-Ressource (XXVIII, 717 p. 254 illus, online resource)
Contents: About the Conference --
Acknowledgement --
Conference Committee --
Editor's Biography --
Preface --
Chapters --
Author Index.
Series Title: Smart Innovation, Systems and Technologies ; 33; SpringerLink : Bücher
Responsibility: edited by Lakhmi C. Jain, Himansu Sekhar Behera, Jyotsna Kumar Mandal, Durga Prasad Mohapatra.

Abstract:

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.

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