Application Scenarios and Basic Structure for Context-Aware Machine Learning Framework

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 2 in Context-Aware Machine Learning and Mobile Data Analytics, 2021, pp 15-22 from Springer

Abstract: Abstract Context-aware machine learning typically focuses on applications that learn from contextual data and develop their decision-making abilities over time. To make intelligent decisions in different context-aware test cases, a structural pipeline based on machine learning techniques is needed to be followed, in which we are interested in this chapter. Before describing the framework, we provide two application scenarios for two different types of social context-aware applications, which motivates research into context-aware machine learning framework and systems. The framework consists of several data processing layers starting from raw contextual data to application development, which has been presented in this chapter.

Keywords: Context-aware computing; System architecture; Machine learning; Smart decision-making; User behavior modeling; Data analytics; Rule-based systems; Intelligent applications (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/978-3-030-88530-4_2

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