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Books on the topic 'Big data analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 October 2024

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1

Chen, Chen, Yuzhuo Ren, and C. C. Jay Kuo. Big Visual Data Analysis. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0631-9.

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2

Ahmed, S., ed. Perspectives on Big Data Analysis. Providence, Rhode Island: American Mathematical Society, 2014. http://dx.doi.org/10.1090/conm/622.

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3

Ahmed, S. Ejaz, ed. Big and Complex Data Analysis. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-41573-4.

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4

Sharma, Rohit, Dilip Kumar Sharma, Dhowmya Bhatt, and Binh Thai Pham. Big Data Analysis for Green Computing. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003032328.

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5

Acharjya, D. P., Satchidananda Dehuri, and Sugata Sanyal, eds. Computational Intelligence for Big Data Analysis. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16598-1.

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6

Zgurovsky, Michael Z., and Yuriy P. Zaychenko. Big Data: Conceptual Analysis and Applications. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-14298-8.

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7

Yang, Dongyuan, and Zhengyu Duan. Assessing Urban Transportation with Big Data Analysis. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3338-7.

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8

Mola, Francesco, Claudio Conversano, and Maurizio Vichi, eds. Classification, (Big) Data Analysis and Statistical Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-55708-3.

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9

Zin, Thi Thi, and Jerry Chun-Wei Lin, eds. Big Data Analysis and Deep Learning Applications. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-0869-7.

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10

Grandinetti, Lucio, Seyedeh Leili Mirtaheri, and Reza Shahbazian, eds. High-Performance Computing and Big Data Analysis. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33495-6.

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11

Mishra, Bhabani Shankar Prasad, Satchidananda Dehuri, Euiwhan Kim, and Gi-Name Wang, eds. Techniques and Environments for Big Data Analysis. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27520-8.

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12

Tanaka-Yamawaki, Mieko, and Yumihiko Ikura. Principal Component Analysis and Randomness Test for Big Data Analysis. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-3967-9.

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13

Dehuri, Satchidananda, and Yen-Wei Chen, eds. Advances in Machine Learning for Big Data Analysis. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8930-7.

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14

Kaya, Mehmet, Jalal Kawash, Suheil Khoury, and Min-Yuh Day, eds. Social Network Based Big Data Analysis and Applications. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78196-9.

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15

Lee, Hyunjoung. Fundamentals of big data: Network analysis for research and industry. Chichester, UK: John Wiley & Sons, 2015.

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16

Dharani, R. Big Data Analysis. Independently Published, 2018.

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17

Hubbard, John R. Java Data Analysis: Data mining, big data analysis, NoSQL, and data visualization. Packt Publishing - ebooks Account, 2017.

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18

SUN CHEN GAO YUN LONG . Big word data analysis Tableau data visualization. People Post Press, 2019.

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19

Spatial Analysis Using Big Data. Elsevier, 2020. http://dx.doi.org/10.1016/c2016-0-02101-0.

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20

Big Data of Complex Networks (Chapman & Hall/CRC Big Data Series). Chapman and Hall/CRC, 2016.

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21

Kitchin, Rob. Data Revolution: A Critical Analysis of Big Data, Open Data and Data Infrastructures. SAGE Publications, Limited, 2021.

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22

Kitchin, Rob. Data Revolution: A Critical Analysis of Big Data, Open Data and Data Infrastructures. SAGE Publications, Limited, 2021.

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23

Abraham, Ajith, Aboul Ella Hassanien, and Mrutyunjaya Panda. Big Data Analytics. Taylor & Francis Group, 2021.

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24

Motai, Yuichi. Data-Variant Kernel Analysis. Wiley & Sons, Incorporated, John, 2015.

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25

Gary King on Big Data Analysis. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2017. http://dx.doi.org/10.4135/9781526459824.

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26

Bhattacharyya, Siddhartha, Hrishikesh Bhaumik, Anirban Mukherjee, and Sourav De, eds. Machine Learning for Big Data Analysis. De Gruyter, 2019. http://dx.doi.org/10.1515/9783110551433.

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27

Sharma, Rohit, Dhowmya Bhatt, Binh Thai Pham, and Dilipa Sarma. Big Data Analysis for Green Computing. Taylor & Francis Group, 2021.

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28

Bhattacharyya, Siddhartha, Sourav De, Anirban Mukherjee, and Hrishikesh Bhaumik. Machine Learning for Big Data Analysis. de Gruyter GmbH, Walter, 2018.

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29

Bhattacharyya, Siddhartha, Sourav De, Anirban Mukherjee, and Hrishikesh Bhaumik. Machine Learning for Big Data Analysis. de Gruyter GmbH, Walter, 2018.

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30

Zgurovsky, Michael Z., and Yuriy P. Zaychenko. Big Data: Conceptual Analysis and Applications. Springer, 2019.

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31

Analysis Of Multivariate And Highdimensional Data. Cambridge University Press, 2013.

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32

Data-Variant Kernel Analysis. Wiley & Sons, Incorporated, John, 2015.

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33

Motai, Yuichi. Data-Variant Kernel Analysis. Wiley & Sons, Limited, John, 2015.

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34

Motai, Yuichi. Data-Variant Kernel Analysis. Wiley & Sons, Incorporated, John, 2015.

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35

Tanaka, Mieko. Principal Component Analysis and Randomness Tests for Big Data Analysis. Springer Japan, 2022.

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36

Koch, Inge. Analysis of Multivariate and High-Dimensional Data. University of Cambridge ESOL Examinations, 2014.

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37

Bouchaud, Jean-Philippe. Random matrix theory and (big) data analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797319.003.0006.

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Abstract:

This chapter reviews methods from random matrix theory to extract information about a large signal matrix C (for example, a correlation matrix arising in big data problems), from its noisy observation matrix M. The chapter shows that the replica method can be used to obtain both the spectral density and the overlaps between noise-corrupted eigenvectors and the true ones, for both additive and multiplicative noise. This allows one to construct optimal rotationally invariant estimators of C based on the observation of M alone. This chapter also discusses the case of rectangular correlation matrices and the problem of random singular value decomposition.

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38

Learning Spark: Lightning-Fast Big Data Analysis. O'Reilly Media, 2015.

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39

Yang, DongYuan, and Zhengyu Duan. Assessing Urban Transportation with Big Data Analysis. Springer, 2022.

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40

Big Data Analysis and Information Technology Systems. Humphries, Elaine, 2022.

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41

Yang, Dongyuan. Assessing Urban Transportation with Big Data Analysis. Springer, 2023.

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42

Tanaka-Yamawaki, Mieko, and Yumihiko Ikura. Principal Component Analysis and Randomness Tests for Big Data Analysis. Springer, 2022.

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43

Big Data Analysis: New Algorithms for a New Society. Springer, 2015.

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44

Ahmed, S. Ejaz. Big and Complex Data Analysis: Methodologies and Applications. Springer London, Limited, 2016.

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45

Ahmed, S. Ejaz. Big and Complex Data Analysis: Methodologies and Applications. Springer, 2018.

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46

Ahmed, S. Ejaz. Big and Complex Data Analysis: Methodologies and Applications. Springer, 2017.

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47

Ossom-Williamson, Peace, and Tiffany B. Kindratt. Big Data for Epidemiology: Applied Data Analysis Using National Health Surveys. Mavs Open Press at UT Arlington, 2022.

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48

Mehta, Rajat. Big Data Analytics with Java: Data analysis, visualization & machine learning techniques. Packt Publishing, 2017.

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49

Matei, Sorin Adam, and Jeff Collmann. Ethical Reasoning in Big Data: An Exploratory Analysis. Springer London, Limited, 2016.

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50

Matei, Sorin Adam, and Jeff Collmann. Ethical Reasoning in Big Data: An Exploratory Analysis. Springer, 2018.

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