Implementing Scalable Machine Learning Algorithms for Mining Big Data: A State-of-the-Art Survey-Reference-Cited by-同舟云学术

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Implementing Scalable Machine Learning Algorithms for Mining Big Data: A State-of-the-Art Survey

Published:2018 Issue: Volume: Page:65-81
ISSN:2197-6503
Container-title:Studies in Big Data
language:
Short-container-title:

Author:

Skënduli Marjana Prifti,Biba Marenglen,Ceci Michelangelo

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-8476-8_4

Reference50 articles.

1. IDC/EMC. (2014, April). The digital universe of opportunities: Rich data and the increasing value of the internet of things. Retrieved from https://www.emc.com/leadership/digital-universe/2014iview/executive-summary.htm .

2. Mashey, J. R. (1999). Retrieved from http://static.usenix.org/event/usenix99/invited_talks/mashey.pdf .

3. Weiss, S., & Indurkhya, N. (1998). Predictive data mining: A practical guide. Morgan.

4. Jin, X., W. Wah, B., Cheng, X., & Wang, Y. (2015). Significance and challenges of Big Data research. Big Data Research, 59–64.

5. Hey, A. J., Tansley, S., & Tolle, K. M. (2009). The fourth paradigm: Data-intensive scientific discovery. WA: Microsoft Research Redmon.

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