東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Techniques and environments for big ...

Mishra, Bhabani Shankar Prasad.

FindBook

Google Book

Amazon

博客來

Techniques and environments for big data analysis = parallel, cloud, and grid computing /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Techniques and environments for big data analysis/ edited by Bhabani Shankar Prasad Mishra ... [et al.].
其他題名:	parallel, cloud, and grid computing /
其他作者:	Mishra, Bhabani Shankar Prasad.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	xi, 191 p. :ill., digital ;24 cm.
內容註:	Introduction to Big Data Analysis -- Parallel Environments -- A Deep Dive into the Hadoop World to Explore its Various Performances -- Natural Language Processing and Machine Learning for Big Data -- Big Data and Cyber Foraging: Future Scope and Challenges -- Parallel GA in Big Data Analysis -- Evolutionary Algorithm Based Techniques to Handle Big Data -- Statistical and Evolutionary Feature Selection Techniques Parallelized using MapReduce Programming Model -- A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop -- The Role of Grid Technologies: A Next Level Combat with Big Data.
Contained By:	Springer eBooks
標題:	Big data. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-27520-8
ISBN:	9783319275208$q(electronic bk.)

Techniques and environments for big data analysis = parallel, cloud, and grid computing /
Techniques and environments for big data analysisparallel, cloud, and grid computing /[electronic resource] :edited by Bhabani Shankar Prasad Mishra ... [et al.]. - Cham :Springer International Publishing :2016. - xi, 191 p. :ill., digital ;24 cm. - Studies in big data,v.172197-6503 ;. - Studies in big data ;v.1..

Introduction to Big Data Analysis -- Parallel Environments -- A Deep Dive into the Hadoop World to Explore its Various Performances -- Natural Language Processing and Machine Learning for Big Data -- Big Data and Cyber Foraging: Future Scope and Challenges -- Parallel GA in Big Data Analysis -- Evolutionary Algorithm Based Techniques to Handle Big Data -- Statistical and Evolutionary Feature Selection Techniques Parallelized using MapReduce Programming Model -- A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop -- The Role of Grid Technologies: A Next Level Combat with Big Data.

This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.

ISBN: 9783319275208$q(electronic bk.)

Standard No.: 10.1007/978-3-319-27520-8doiSubjects--Topical Terms:

2045508
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Techniques and environments for big data analysis = parallel, cloud, and grid computing /
LDR:02215nmm a2200325 a 4500 001 2030860
003 DE-He213
005 20160824151404.0
006 m d
007 cr nn 008maaau
008 160908s2016 gw s 0 eng d
020 $a 9783319275208$q(electronic bk.)
020 $a 9783319275185$q(paper)
024 7 $a 10.1007/978-3-319-27520-8 $2 doi
035 $a 978-3-319-27520-8
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 T255 2016
245 0 0 $a Techniques and environments for big data analysis $h [electronic resource] : $b parallel, cloud, and grid computing / $c edited by Bhabani Shankar Prasad Mishra ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xi, 191 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6503 ; $v v.17
505 0 $a Introduction to Big Data Analysis -- Parallel Environments -- A Deep Dive into the Hadoop World to Explore its Various Performances -- Natural Language Processing and Machine Learning for Big Data -- Big Data and Cyber Foraging: Future Scope and Challenges -- Parallel GA in Big Data Analysis -- Evolutionary Algorithm Based Techniques to Handle Big Data -- Statistical and Evolutionary Feature Selection Techniques Parallelized using MapReduce Programming Model -- A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop -- The Role of Grid Technologies: A Next Level Combat with Big Data.
520 $a This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.
650 0 $a Big data. $3 2045508
650 0 $a Data structures (Computer science) $3 527210
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
700 1 $a Mishra, Bhabani Shankar Prasad. $3 2182911
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in big data ; $v v.1. $3 2055170
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-27520-8
950 $a Engineering (Springer-11647)