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Context-Aware Rule-Based Expert System Modeling

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

An expert system is a computer system that simulates the decision-making abilities of a human expert in artificial intelligence (AI). Expert systems, rather than using traditional procedural code, are structured to solve complex problems by reasoning through sources of knowledge, which are primarily interpreted as if–then rules. In this chapter, we explore primarily on context-aware rule-based expert system modeling, which is considered one of the key AI techniques that can be used to make intelligent decisions and more powerful mobile applications. Hence, we discuss mobile expert system as a knowledge or rule-based modeling, where a set of context-aware rules are extracted from mobile data discussed in earlier chapters. We have also explored how machine learning based context-aware rules can be used in an effective expert system modeling rather than hardcoded rules created by human experts, within the area of context-aware computing and intelligent mobile applications.

Suggested Citation

  • Iqbal H. Sarker & Alan Colman & Jun Han & Paul Watters, 2021. "Context-Aware Rule-Based Expert System Modeling," Springer Books, in: Context-Aware Machine Learning and Mobile Data Analytics, chapter 0, pages 129-136, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-88530-4_8
    DOI: 10.1007/978-3-030-88530-4_8
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