Context-Aware Machine Learning System: Applications and Challenging Issues

Iqbal H. Sarker, Alan Colman, Jun Han and Paul Watters
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Iqbal H. Sarker: Swinburne University of Technology
Alan Colman: Swinburne University of Technology
Jun Han: Swinburne University of Technology
Paul Watters: Macquarie University

Chapter Chapter 10 in Context-Aware Machine Learning and Mobile Data Analytics, 2021, pp 147-157 from Springer

Abstract: Abstract Context-awareness has recently received much attention in academia and industry for a variety of applications. Due to its intelligence in technologies and availability in various real-world applications, there has been a lot of development in the domain of context-aware computing systems in recent years. However, building a context-aware machine learning system still poses a variety of genuine challenges. This chapter addresses the most important and vital issues, ranging from contextual data collection to decision-making, that has been thoroughly explored in the earlier chapters of this book. In terms of new research perspective, future advances in industries or academia, or smart solutions in context-aware technology, prospective research works and challenges in the field of context-aware computing have been addressed in this chapter. Before discussing the challenging issues, we have summarized several real-world context-aware applications that intelligently assist individual smartphone users in their everyday activities as well as motivates to work in this area.

Keywords: Smartphone user; Mobile data analytics; Machine learning; User behavior modeling; Context-aware system; Rule-base system; Intelligent applications (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-88530-4_10

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DOI: 10.1007/978-3-030-88530-4_10

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