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  • 2015-2019  (2)
  • Waltham, MA : Morgan Kaufmann  (2)
  • Big Data  (2)
  • Computer science
  • Computer Science  (2)
Datasource
Material
Language
Years
  • 2015-2019  (2)
Year
Author, Corporation
Subjects(RVK)
  • Computer Science  (2)
  • 1
    Online Resource
    Online Resource
    Waltham, MA : Morgan Kaufmann
    ISBN: 9780128008676 , 9780128011317 (Sekundärausgabe) , 0128011319 (Sekundärausgabe)
    Language: English
    Edition: First edition
    Edition: Online-Ausg. Sebastopol, CA O'Reilly Media Inc. Online-Ressource Safari Tech Books Online ISBN 9780128011317 Online
    Edition: ISBN 0128011319 Online
    Edition: [Online-Ausg.]
    DDC: 004.7
    RVK:
    RVK:
    Keywords: Social Media ; Data Mining ; Big Data
    Note: Online-Ausg.:
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    ISBN: 9780128011317 , 0128011319 , 0128008679 , 9780128008676
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition
    Parallel Title: Erscheint auch als
    DDC: 004.7
    RVK:
    Keywords: COMPUTERS / Computer Literacy ; COMPUTERS / Computer Science ; COMPUTERS / Data Processing ; COMPUTERS / Hardware / General ; COMPUTERS / Information Technology ; COMPUTERS / Machine Theory ; COMPUTERS / Reference ; Big data ; Data mining ; Social media ; Cloud computing ; Computer software / Development ; Distributed operating systems (Computers) ; Social media ; Data mining ; Big data ; Data Mining ; Social Media ; Big Data ; Social Media ; Data Mining ; Big Data
    Abstract: Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion
    Note: Includes bibliographical references and index
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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