國立虎尾科技大學 |

Computational Intelligence in Data Mining - Volume 1 = Proceedings of the International Conference on CIDM, 20-21 December 2014 /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Computational Intelligence in Data Mining - Volume 1/ edited by Lakhmi C. Jain, Himansu Sekhar Behera, Jyotsna Kumar Mandal, Durga Prasad Mohapatra.
Reminder of title:	Proceedings of the International Conference on CIDM, 20-21 December 2014 /
other author:	Jain, Lakhmi C.
Description:	XXVIII, 713 p. 327 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-81-322-2205-7
ISBN:	9788132222057

Computational Intelligence in Data Mining - Volume 1 = Proceedings of the International Conference on CIDM, 20-21 December 2014 /
Computational Intelligence in Data Mining - Volume 1Proceedings of the International Conference on CIDM, 20-21 December 2014 /[electronic resource] :edited by Lakhmi C. Jain, Himansu Sekhar Behera, Jyotsna Kumar Mandal, Durga Prasad Mohapatra. - 1st ed. 2015. - XXVIII, 713 p. 327 illus.online resource. - Smart Innovation, Systems and Technologies,312190-3018 ;. - Smart Innovation, Systems and Technologies,37.

About the Conference -- Acknowledgement.- Conference Committee.- Editor's Biography.- Preface.- Table of Contents -- Chapters -- Author Index.

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.

ISBN: 9788132222057

Standard No.: 10.1007/978-81-322-2205-7doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Computational Intelligence in Data Mining - Volume 1 = Proceedings of the International Conference on CIDM, 20-21 December 2014 /
LDR:02704nam a22004095i 4500 001 967685
003 DE-He213
005 20200629192933.0
007 cr nn 008mamaa
008 201211s2015 ii | s |||| 0|eng d
020 $a 9788132222057 $9 978-81-322-2205-7
024 7 $a 10.1007/978-81-322-2205-7 $2 doi
035 $a 978-81-322-2205-7
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Computational Intelligence in Data Mining - Volume 1 $h [electronic resource] : $b Proceedings of the International Conference on CIDM, 20-21 December 2014 / $c edited by Lakhmi C. Jain, Himansu Sekhar Behera, Jyotsna Kumar Mandal, Durga Prasad Mohapatra.
250 $a 1st ed. 2015.
264 1 $a New Delhi : $b Springer India : $b Imprint: Springer, $c 2015.
300 $a XXVIII, 713 p. 327 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Smart Innovation, Systems and Technologies, $x 2190-3018 ; $v 31
505 0 $a About the Conference -- Acknowledgement.- Conference Committee.- Editor's Biography.- Preface.- Table of Contents -- Chapters -- Author Index.
520 $a 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.
650 0 $a Computational intelligence. $3 568984
650 0 $a Data mining. $3 528622
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Artificial Intelligence. $3 646849
700 1 $a Jain, Lakhmi C. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 671306
700 1 $a Behera, Himansu Sekhar. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1104148
700 1 $a Mandal, Jyotsna Kumar. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1208238
700 1 $a Mohapatra, Durga Prasad. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1023158
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9788132222064
776 0 8 $i Printed edition: $z 9788132222040
776 0 8 $i Printed edition: $z 9788132229896
830 0 $a Smart Innovation, Systems and Technologies, $x 2190-3018 ; $v 37 $3 1255196
856 4 0 $u https://doi.org/10.1007/978-81-322-2205-7
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)