國立高雄大學圖資館 |

Language: English

Back

Data science and big data analyticsA...

(1998 :)

Data science and big data analyticsACM-WIR 2018 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data science and big data analyticsedited by Durgesh Kumar Mishra, Xin-She Yang, Aynur Unal.
Reminder of title:	ACM-WIR 2018 /
remainder title:	ACM-WIR 2018
other author:	Mishra, Durgesh Kumar.
corporate name:
Published:	Singapore :Springer Singapore :2019.
Description:	xxiv, 406 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Big dataCongresses.
Online resource:	http://dx.doi.org/10.1007/978-981-10-7641-1
ISBN:	9789811076411$q(electronic bk.)

Data science and big data analyticsACM-WIR 2018 /
Data science and big data analyticsACM-WIR 2018 /[electronic resource] :ACM-WIR 2018edited by Durgesh Kumar Mishra, Xin-She Yang, Aynur Unal. - Singapore :Springer Singapore :2019. - xxiv, 406 p. :ill., digital ;24 cm. - Lecture notes on data engineering and communications technologies,v.162367-4512 ;. - Lecture notes on data engineering and communications technologies ;v.2..

This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.

ISBN: 9789811076411$q(electronic bk.)

Standard No.: 10.1007/978-981-10-7641-1doiSubjects--Topical Terms:

592065
Big data
--Congresses.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Data science and big data analyticsACM-WIR 2018 /
LDR:01740nmm a2200325 a 4500 001 551367
003 DE-He213
005 20180801151152.0
006 m d
007 cr nn 008maaau
008 191024s2019 si s 0 eng d
020 $a 9789811076411$q(electronic bk.)
020 $a 9789811076404$q(paper)
024 7 $a 10.1007/978-981-10-7641-1 $2 doi
035 $a 978-981-10-7641-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.B45
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 005.7 $2 23
090 $a QA76.9.B45 $b A184 2018
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Data science and big data analytics $h [electronic resource] : $b ACM-WIR 2018 / $c edited by Durgesh Kumar Mishra, Xin-She Yang, Aynur Unal.
246 3 $a ACM-WIR 2018
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xxiv, 406 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes on data engineering and communications technologies, $x 2367-4512 ; $v v.16
520 $a This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.
650 0 $a Big data $v Congresses. $3 592065
650 0 $a Data mining $v Congresses. $3 380776
650 0 $a Machine learning $v Congresses. $3 384498
650 1 4 $a Engineering. $3 210888
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Big Data. $3 760530
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Systems and Data Security. $3 274481
700 1 $a Mishra, Durgesh Kumar. $3 801401
700 1 $a Yang, Xin-She. $3 522569
700 1 $a Unal, Aynur. $3 764263
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Lecture notes on data engineering and communications technologies ; $v v.2. $3 770548
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-7641-1
950 $a Engineering (Springer-11647)