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Modern technologies for big data cla...

Murty, M. Narasimha,

Modern technologies for big data classification and clustering[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	005.7
書名/作者:	Modern technologies for big data classification and clustering/ Hari Seetha, M. Narasimha Murty, and B.K. Tripathy, editors.
其他作者:	Seetha, Hari,
出版者:	Hershey, Pennsylvania : : IGI Global,, [2018]
面頁冊數:	1 online resource (xxi, 360 p.)
標題:	Big data.
標題:	Data mining.
標題:	Cluster analysis.
標題:	Classification - Nonbook materials.
標題:	Document clustering.
ISBN:	9781522528067 (ebook)
ISBN:	9781522528050 (hardcover)
書目註:	Includes bibliographical references and index.
內容註:	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.
摘要、提要註:	"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"--
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2805-0

Modern technologies for big data classification and clustering[electronic resource] /
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:

571002
Big data.

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

Dewey Class. No.: 005.7

Modern technologies for big data classification and clustering[electronic resource] /
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006 m o d
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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 571002
650 0 $a Data mining. $3 337740
650 0 $a Cluster analysis. $3 488617
650 0 $a Classification $x Nonbook materials. $3 733084
650 0 $a Document clustering. $3 639204
700 1 $a Seetha, Hari, $d 1970- $e editor. $3 733082
700 1 $a Murty, M. Narasimha, $e editor. $3 733083
700 1 $a Tripathy, B. K., $d 1957- $e editor. $3 570988
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2805-0

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