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Deep Learning for Contextual Mobile Data Analytics

In: Context-Aware Machine Learning and Mobile Data Analytics

Author

Listed:
  • Iqbal H. Sarker

    (Swinburne University of Technology
    Chittagong University of Engineering & Technology)

  • Alan Colman

    (Swinburne University of Technology)

  • Jun Han

    (Swinburne University of Technology)

  • Paul Watters

    (Macquarie University
    Cyberstronomy Pty Ltd)

Abstract

Deep learning is considered as a part of the broader family of machine learning methods, which is based on artificial neural networks with representation learning. In the earlier chapters, we have presented methodologies to build context-aware machine learning systems through pre-processing steps of contextual raw data, extracting contextual rules, recent pattern-based rule updating and management, as well as rule-based expert system modeling and related issues. Although, the rule-based machine learning methods performed well in this regard discussed in the earlier chapters, deep learning can be used when a large amount of data is available. This chapter discusses the importance of deep learning and a deep learning based context-aware model for mobile phone users.

Suggested Citation

  • Iqbal H. Sarker & Alan Colman & Jun Han & Paul Watters, 2021. "Deep Learning for Contextual Mobile Data Analytics," Springer Books, in: Context-Aware Machine Learning and Mobile Data Analytics, chapter 0, pages 137-146, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-88530-4_9
    DOI: 10.1007/978-3-030-88530-4_9
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