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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.

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Inhoudsopgave

1. Introduction2. Social Sensing Trends and Applications3. Mathematical Foundations4. Basic Fact-Finding5. Maximum Likelihood Estimation6. Confidence Bounds7. Conflicting Observations and Non-Binary Claims8. Understanding the Social Network9. Understanding Physical Dependencies10. Recursive Fact-finding11. Privacy12. Further Readings13. Conclusions and Remaining Challenges

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€ 87,34
Levertijd ongeveer 9 werkdagen
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          Social Sensing