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Social big data mining / Hiroshi Ishikawa.

By: Ishikawa, Hiroshi [author.].
Material type: TextTextPublisher: Boca Raton: CRC Press, ©2015Description: vi, 260 p. : illustrations ; 25 cm.ISBN: 9781498710930.Subject(s): Data mining | Big data | User-generated content | Social mediaDDC classification: 006.312
Contents:
1. Social media -- 2. Big data and social data -- 3. Hyptheses in the era of big data -- 4. Social big data applications -- 5. Basic concepts in data mining -- 6. Association rule mining -- 7. Clustering -- 8. Classification -- 9. Prediction -- 10. Web structure mining -- 11. Web content mining -- 12. Web access log mining, information extraction, and deep web mining -- 13. Media mining -- 14. Scalability and outlier detection.
Summary: This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains analytical techniques such as modeling, data mining, and multivariate analysis for social big data.
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Item type Current location Call number Status Date due Barcode Item holds
Books Books ISI Library, Kolkata
 
006.312 Is79 (Browse shelf) Available 137328
Total holds: 0

Includes bibliographical references and index.

1. Social media --
2. Big data and social data --
3. Hyptheses in the era of big data --
4. Social big data applications --
5. Basic concepts in data mining --
6. Association rule mining --
7. Clustering --
8. Classification --
9. Prediction --
10. Web structure mining --
11. Web content mining --
12. Web access log mining, information extraction, and deep web mining --
13. Media mining --
14. Scalability and outlier detection.

This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains analytical techniques such as modeling, data mining, and multivariate analysis for social big data.

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