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Autor(en): 
  • Paul Watters
  • Jun Han
  • Alan Colman
  • Iqbal Sarker
  • Context-Aware Machine Learning and Mobile Data Analytics: Automated Rule-based Services with Intelligent Decision-Making 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Dezember 2021  
    Genre:  EDV / Informatik 
     
    App-Programmierung, Programmierung für Mobil-Geräte / associationrules / context-awaremobilecomputing / Data Mining / machinelearning / Maschinelles Lernen / Mobiledataanalytics / personalization
    ISBN:  9783030885298 
    EAN-Code: 
    9783030885298 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 241 mm / B 160 mm / D 16 mm 
    Gewicht:  436 gr 
    Seiten:  176 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      



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