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Big Data Analytics: A Cognitive Perspectives

Big Data Analytics: A Cognitive Perspectives

Yingxu Wang, Jun Peng
Copyright: © 2017 |Volume: 11 |Issue: 2 |Pages: 16
ISSN: 1557-3958|EISSN: 1557-3966|EISBN13: 9781522511700|DOI: 10.4018/IJCINI.2017040103
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MLA

Wang, Yingxu, and Jun Peng. "Big Data Analytics: A Cognitive Perspectives." IJCINI vol.11, no.2 2017: pp.41-56. http://doi.org/10.4018/IJCINI.2017040103

APA

Wang, Y. & Peng, J. (2017). Big Data Analytics: A Cognitive Perspectives. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 11(2), 41-56. http://doi.org/10.4018/IJCINI.2017040103

Chicago

Wang, Yingxu, and Jun Peng. "Big Data Analytics: A Cognitive Perspectives," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 11, no.2: 41-56. http://doi.org/10.4018/IJCINI.2017040103

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Abstract

Big data are pervasively generated by human cognitive processes, formal inferences, and system quantifications. This paper presents the cognitive foundations of big data systems towards big data science. The key perceptual model of big data systems is the recursively typed hyperstructure (RTHS). The RTHS model reveals the inherited complexities and unprecedented difficulty in big data engineering. This finding leads to a set of mathematical and computational models for efficiently processing big data systems. The cognitive relationship between data, information, knowledge, and intelligence is formally described.

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