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Embedding Intelligence Within Data Points for a Machine Learning Framework: “Hex-Elementization”

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Intelligent Systems and Applications (IntelliSys 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1037))

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Abstract

This paper presents a unique concept of Hex-Elementization (Hex-E) that is applied to data points in order to enable increasingly sophisticated utilization of big data. The premise of this paper is to define data points through 6 attributes which “learn” to connect automatically with other data points through Machine Learning (ML) resulting in suites of analytics. These analytics can grow in multiple directions depending on the needs of the business and the intelligence encoded within the data points through the Hex-E framework. This paper is part of ongoing research that is following a mixed-methods approach to propose, develop and validate Hex-E.

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Author information

Authors and Affiliations

  1. University of South Florida, Sarasota-Manatee, Sarasota, FL, 34242, USA

    Bhuvan Unhelkar

  2. Western Sydney University, Sydney, Australia

    Girish Nair

Authors
  1. Bhuvan Unhelkar
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  2. Girish Nair
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Corresponding author

Correspondence to Bhuvan Unhelkar .

Editor information

Editors and Affiliations

  1. School of Computing, Computer Science Research Institute, Ulster University, Newtownabbey, UK

    Yaxin Bi

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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Unhelkar, B., Nair, G. (2020). Embedding Intelligence Within Data Points for a Machine Learning Framework: “Hex-Elementization”. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_47

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