Integrating machine learning technology to data analytics for e-commerce on cloud

John Yeung, Simon Wong, Alvin Tam, Joseph So

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

This paper presents the technical challenges faced by e-commerce players and how cloud computing has been designed and developed to handle these technical challenges. Once these technical challenges have been handled, another challenge of building data analytics on cloud platforms come out. This paper also highlights the main reasons of driving organizations to build data analytics on cloud. Besides, this paper exhibits how to integrate machine learning models to the data analytic processes, for making more sophisticated analysis for e-commerce activities. The platform Amazon SageMaker is adopted to illustrate how machine learning models were integrated in the data analytic processes. The public cloud platform Amazon Web Services is used to present how machine learning models were integrated in the practices with a real-life c-commerce case.

Original languageEnglish
Title of host publicationProceedings of the 3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019
EditorsXin-She Yang, Nilanjan Dey, Amit Joshi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages105-109
Number of pages5
ISBN (Electronic)9781728137803
DOIs
Publication statusPublished - Jul 2019
Event3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019 - London, United Kingdom
Duration: 30 Jul 201931 Jul 2019

Publication series

NameProceedings of the 3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019

Conference

Conference3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019
Country/TerritoryUnited Kingdom
CityLondon
Period30/07/1931/07/19

Keywords

  • Cloud Computing
  • Data Analytics
  • E-Commerce
  • Machine Learning

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