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Autor(en): 
  • Cyrus Shahabi
  • Lei Chen
  • Yongxin Tong
  • Yuxiang Zeng
  • Zimu Zhou
  • Spatial Crowdsourcing 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (September 2026)  
    Genre:  Schulbücher 
     
    Crowdsourcing Data / Data and Information Visualization / Data Incentive Mechanism / Data Mining / Data Mining and Knowledge Discovery / Data quality control / Data Science / Data Warehousing
    ISBN:  9783032322753 
    EAN-Code: 
    9783032322753 
    Verlag:  Springer International Publishing 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 240 mm / B 168 mm / D  
    Seiten:  116 
    Illustration:  XIV, 116 p. 31 illus., 25 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    This book explores the essential computing paradigm of crowdsourcing, particularly the rise in utility and application of crowdsourced spatiotemporal data. This book begins with an overview of how the ubiquity of mobile internet services and the growth of the sharing economy have created ideal conditions for the growth of spatial crowdsourcing, why humans are ideal contributors to spatiotemporal tasks that must be completed at specific locations and times, and the core challenges of crowdsourcing that data. Readers then get a deeper dive into practical application issues. In particular, this book centers on identifying four core algorithmic issues in spatial crowdsourcing: (1) task assignment, (2) quality control, (3) incentive mechanism design, and (4) privacy protection. Readers find this books contains a comprehensive and systematic review of existing research on these issues and analyzes representative spatial crowdsourcing applications with explanations of how those four technical issues enable them. This book describes a number of real-life examples that demonstrate recent successes, techniques, and specific challenges in crowdsourcing for applications that provide urban services, such as ride sharing and live-mapping. Finally, this book discusses open questions that need to be addressed in future spatial crowdsourcing research and applications.

      



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