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Distributed Computing in Cognitive Analytics

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Distributed Computing in Big Data Analytics

Part of the book series: Scalable Computing and Communications ((SCC))

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Abstract

“Cognitive Analytics” used to be the phrase popular in academia and scientific circles until recently with very limited utilization within specialized industries such as travel and transport. However, in last year or two this phrase has gone viral across various business industries with experts predicting that the cognitive systems will play a very vital role in next generation of computing in general and especially in Big Data Analytics. In this chapter we will discuss importance and impact of Distributed Computing for Cognitive analysis followed by industry adoption and patterns observed. The chapter introduces various aspects of cognitive systems including the key components to build such systems. The chapter will also cover evolution of various technologies and methodologies in the cognitive analytics space. Finally we will discuss specific use cases being implemented currently in the enterprises in the areas of Health Care, Internet Of Things and Customer Care.

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References

  1. “Cognitive.” Merriam-Webster.com . Merriam-Webster, n.d. Web. 18 Feb. 2017.

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  4. Kenneth Jensen, 2013. CRISP-DM. retrieved from https://commons.wikimedia.org/wiki/File:CRISP-DM_Process_Diagram.png.

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Correspondence to Vishwanath Kamat .

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Kamat, V. (2017). Distributed Computing in Cognitive Analytics. In: Mazumder, S., Singh Bhadoria, R., Deka, G. (eds) Distributed Computing in Big Data Analytics. Scalable Computing and Communications. Springer, Cham. https://doi.org/10.1007/978-3-319-59834-5_7

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  • DOI: https://doi.org/10.1007/978-3-319-59834-5_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59833-8

  • Online ISBN: 978-3-319-59834-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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