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Modern technologies for big data classification and clustering

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Modern technologies for big data classification and clustering/ Hari Seetha, M. Narasimha Murty, and B.K. Tripathy, editors.
other author:	Seetha, Hari,
Published:	Hershey, Pennsylvania :IGI Global, : [2018],
Description:	1 online resource (xxi, 360 p.)
基督教聖經之智慧書導讀 :	"This book provides an analysis of large data in the field of classification and clustering by presenting algorithms and comparative analysis in the form of their effectiveness and efficiency. It covers topics such as handling large data with conventional data mining, machine learning algorithms and information about new technologies, algorithms and platforms developed for handling large data"--
Subject:	Big data. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2805-0
ISBN:	9781522528067 (ebook)

Modern technologies for big data classification and clustering
Modern technologies for big data classification and clustering[electronic resource] /Hari Seetha, M. Narasimha Murty, and B.K. Tripathy, editors. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xxi, 360 p.)

Includes bibliographical references and index.

Chapter 1. Uncertainty-based clustering algorithms for large data sets -- Chapter 2. Sentiment mining approaches for big data classification and clustering -- Chapter 3. Data compaction techniques -- Chapter 4. Methodologies and technologies to retrieve information from text sources -- Chapter 5. Twitter data analysis -- Chapter 6. Use of social network analysis in telecommunication domain -- Chapter 7. A review on spatial big data analytics and visualization -- Chapter 8. A survey on overlapping communities in large-scale social networks -- Chapter 9. A brief study of approaches to text feature selection -- Chapter 10. Biological big data analysis and visualization: a survey.

Restricted to subscribers or individual electronic text purchasers.

"This book provides an analysis of large data in the field of classification and clustering by presenting algorithms and comparative analysis in the form of their effectiveness and efficiency. It covers topics such as handling large data with conventional data mining, machine learning algorithms and information about new technologies, algorithms and platforms developed for handling large data"--

ISBN: 9781522528067 (ebook)Subjects--Topical Terms:

387512
Big data.

LC Class. No.: QA76.9.B45 / M63 2018e

Dewey Class. No.: 005.7

Modern technologies for big data classification and clustering
LDR:02114nam a2200277 a 4500 001 314496
003 IGIG
005 20181028102016.0
006 m o d
007 cr cn
008 181108s2018 pau fob 001 0 eng d
010 $z 2017010783
020 $a 9781522528067 (ebook)
020 $a 9781522528050 (hardcover)
035 $a (OCoLC)988619713
035 $a 1071025284
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
050 4 $a QA76.9.B45 $b M63 2018e
082 0 4 $a 005.7 $2 23
245 0 0 $a Modern technologies for big data classification and clustering $h [electronic resource] / $c Hari Seetha, M. Narasimha Murty, and B.K. Tripathy, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2018]
300 $a 1 online resource (xxi, 360 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Uncertainty-based clustering algorithms for large data sets -- Chapter 2. Sentiment mining approaches for big data classification and clustering -- Chapter 3. Data compaction techniques -- Chapter 4. Methodologies and technologies to retrieve information from text sources -- Chapter 5. Twitter data analysis -- Chapter 6. Use of social network analysis in telecommunication domain -- Chapter 7. A review on spatial big data analytics and visualization -- Chapter 8. A survey on overlapping communities in large-scale social networks -- Chapter 9. A brief study of approaches to text feature selection -- Chapter 10. Biological big data analysis and visualization: a survey.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book provides an analysis of large data in the field of classification and clustering by presenting algorithms and comparative analysis in the form of their effectiveness and efficiency. It covers topics such as handling large data with conventional data mining, machine learning algorithms and information about new technologies, algorithms and platforms developed for handling large data"-- $c Provided by publisher.
650 0 $a Big data. $3 387512
650 0 $2 96060 $a Data mining. $3 255525
650 0 $a Cluster analysis. $3 433502
650 0 $a Classification $x Nonbook materials. $3 433503
650 0 $a Document clustering. $3 433504
700 1 $a Seetha, Hari, $d 1970- $e editor. $3 433499
700 1 $a Murty, M. Narasimha, $e editor. $3 433500
700 1 $a Tripathy, B. K., $d 1957- $e editor. $3 433501
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2805-0

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