Social Sensing: Building Reliable Systems on Unreliable Data

✍ Scribed by Dong Wang, Tarek Abdelzaher, Lance Kaplan

• Publisher: Morgan Kaufmann
• Year: 2015
• Tongue: English
• Leaves: 219
• Edition: 1
• Category: Library

✦ Synopsis

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

✦ Table of Contents

Content:
Front Matter, Pages i-ii
Copyright, Page iv
Dedication, Page v
Acknowledgments, Pages xi-xii
Authors, Pages xiii-xiv
Foreword, Pages xv-xvi
Preface, Pages xvii-xviii
Chapter 1 - A new information age, Pages 1-11
Chapter 2 - Social sensing trends and applications, Pages 13-20
Chapter 3 - Mathematical foundations of social sensing: An introductory tutorial, Pages 21-36
Chapter 4 - Fact-finding in information networks, Pages 37-55
Chapter 5 - Social Sensing: A maximum likelihood estimation approach, Pages 57-77
Chapter 6 - Confidence bounds in social sensing, Pages 79-104
Chapter 7 - Resolving conflicting observations and non-binary claims, Pages 105-127
Chapter 8 - Understanding the social network, Pages 129-151
Chapter 9 - Understanding physical dependencies: Social meets cyber-physical, Pages 153-170
Chapter 10 - Recursive fact-finding, Pages 171-183
Chapter 11 - Further readings, Pages 185-190
Chapter 12 - Conclusions and future challenges, Pages 191-196
References, Pages 197-208
Index, Pages 209-213