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Big Data Analytics: A Cognitive Perspectives

Author

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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)

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.

Suggested Citation

  • Yingxu Wang & Jun Peng, 2017. "Big Data Analytics: A Cognitive Perspectives," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 11(2), pages 41-56, April.
    • Handle: RePEc:igg:jcini0:v:11:y:2017:i:2:p:41-56
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    Cited by:

    1. Sophie Wintersberger & Muhammad Azmat & Sebastian Kummer, 2019. "Are We Ready to Ride Autonomous Vehicles? A Pilot Study on Austrian Consumers’ Perspective," Logistics, MDPI, vol. 3(4), pages 1-20, September.
    2. Muhammad Azmat & Sebastian Kummer & Lara Trigueiro Moura & Federico Di Gennaro & Rene Moser, 2019. "Future Outlook of Highway Operations with Implementation of Innovative Technologies Like AV, CV, IoT and Big Data," Logistics, MDPI, vol. 3(2), pages 1-20, June.

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