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Modern technologies for big data classification and clustering /

"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 algorithm...

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Bibliographic Details
Other Authors: Seetha, Hari, 1970- (Editor), Murty, M. Narasimha, (Editor), Tripathy, B. K., 1957- (Editor)
Format: eBook
Language:English
Published: Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global, [2018]
Subjects:
Big data.
Data mining.
Cluster analysis.
Classification > Nonbook materials.
Document clustering.
Online Access:View fulltext via EzAccess
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020 |z 9781522528050  |q hardcover 
020 |a 9781522528067  |q ebook 
024 7 |a 10.4018/978-1-5225-2805-0  |2 doi 
035 |a (CaBNVSL)slc19713224 
035 |a (OCoLC)988619713 
040 |a CaBNVSL  |b eng  |e rda  |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 /  |c Hari Seetha, M. Narasimha Murty, and B.K. Tripathy, editors. 
264 1 |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) :  |b IGI Global,  |c [2018] 
300 |a 15 PDFs (xxi, 360 pages) 
336 |a text  |2 rdacontent 
337 |a electronic  |2 isbdmedia 
338 |a online resource  |2 rdacarrier 
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. 
530 |a Also available in print. 
538 |a Mode of access: World Wide Web. 
588 |a Description based on title screen (IGI Global, viewed 07/18/2017). 
650 0 |a Big data. 
650 0 |a Data mining. 
650 0 |a Cluster analysis. 
650 0 |a Classification  |x Nonbook materials. 
650 0 |a Document clustering. 
700 1 |a Seetha, Hari,  |d 1970-  |e editor. 
700 1 |a Murty, M. Narasimha,  |e editor. 
700 1 |a Tripathy, B. K.,  |d 1957-  |e editor. 
710 2 |a IGI Global,  |e publisher. 
776 0 |c (Original)  |w (DLC)2017010783 
776 0 8 |i Print version:  |z 1522528059  |z 9781522528050  |w (DLC) 2017010783 
856 4 1 |z View fulltext via EzAccess  |u https://ezaccess.library.uitm.edu.my/login?url=http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-2805-0 

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