Social Sensing (ePub)

Name: Social Sensing
Brand: Elsevier Science & Techn.
SKU: 67301531
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Building Reliable Systems on Unreliable Data (Sprache: Englisch)

Autoren: Dong Wang , Tarek Abdelzaher , Lance Kaplan

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Social Sensing, Dong Wang, Tarek Abdelzaher, Lance Kaplan

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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...

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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.

Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability
Presents novel theoretical foundations for assured social sensing and modeling humans as sensors
Includes case studies and application examples based on real data sets
Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book

Autoren-Porträt von Dong Wang, Tarek Abdelzaher, Lance Kaplan

Dong Wang is an Assistant Professor at the Department of Computer Science and Engineering, the University of Notre Dame. He received his Ph.D. in Computer Science from University of Illinois at Urbana Champaign (UIUC) in 2012, an M.S. degree from Peking University in 2007 and a B.Eng. from the University of Electronic Science and Technology of China in 2004, respectively. Dong Wang has published over 30 technical papers in conferences and journals, including IPSN, ICDCS, IEEE JSAC, IEEE J-STSP, and ACM ToSN. His research on social sensing resulted in software tools that found applications in academia, industry, and government research labs. His work was widely reported in talks, keynotes, panels, and tutorials, including at IBM Research, ARL, CPSWeek, RTSS, IPSN, and the University of Michigan, to name a few. Wang's interests lie in developing analytic foundations for reliable information distillation systems, as well as the foundations of data credibility analysis, in the face of noise and conflicting observations, where evidence is collected by both humans and machines.

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Bibliographische Angaben

Autoren: Dong Wang , Tarek Abdelzaher , Lance Kaplan
2015, 232 Seiten, Englisch
Verlag: Elsevier Science & Techn.
ISBN-10: 0128011319
ISBN-13: 9780128011317
Erscheinungsdatum: 17.04.2015

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Dateiformat: ePub
Grösse: 16 MB
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"...recommended both to cyber-physical systems researchers and sensor network researchers, but also to people involved in business analytics. After finishing this book, readers will better understand the fundamental concepts related to the subject and also receive new interpretations of, and solutions to, the problems encountered." --Computing Reviews

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