Big Data Analytics: A Cognitive Perspectives

Yingxu Wang and Jun Peng
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Yingxu Wang: Chongqing University of Science and Technology, School of Electrical and Information Engineering, Chongqing, China
Jun Peng: Chongqing University of Science and Technology, School of Electrical and Information Engineering, Chongqing, China

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2017, vol. 11, issue 2, 41-56

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.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jcini0:v:11:y:2017:i:2:p:41-56

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