Context-Aware Machine Learning and Mobile Data Analytics: Automated Rule-Based Services with Intelligent Decision-Making

By Alan Colman, Iqbal Sarker, Jun Han

This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the applicationdevelopers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.

• Format: Paperback
• Language: English
• ISBN: 3030885321
• ISBN13: 9783030885328
• Release Date: December 2022
• Publisher: Springer
• Length: 157 Pages
• Weight: 0.56 lbs.
• Dimensions: 0.4" x 6.1" x 9.2"