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Computational Intelligence in Data Mining - Volume 2 [electronic resource] : Proceedings of the International Conference on CIDM, 20-21 December 2014 / edited by Lakhmi C. Jain, Himansu Sekhar Behera, Jyotsna Kumar Mandal, Durga Prasad Mohapatra.

Contributor(s): Jain, Lakhmi C [editor.] | Behera, Himansu Sekhar [editor.] | Mandal, Jyotsna Kumar [editor.] | Mohapatra, Durga Prasad [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Smart Innovation, Systems and Technologies: 32Publisher: New Delhi : Springer India : Imprint: Springer, 2015Description: XXVIII, 707 p. 276 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9788132222088.Subject(s): Engineering | Data mining | Computers | Computational intelligence | Engineering | Computational Intelligence | Data Mining and Knowledge Discovery | Computing MethodologiesAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
About the Conference -- Acknowledgement -- Conference Committee -- Editor's Biography -- Preface -- Chapters -- Author Index.
In: Springer eBooksSummary: The contributed volume aims to explicate and address the difficulties and challenges that of seamless integration of the 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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About the Conference -- Acknowledgement -- Conference Committee -- Editor's Biography -- Preface -- Chapters -- Author Index.

The contributed volume aims to explicate and address the difficulties and challenges that of seamless integration of the 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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