Social Sensing Building Reliable Systems Unreliable Data Dong Wang Paperback

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Last updated on Mar 09, 2025 01:56:31 SGTView all revisionsView all revisions

Item specifics

Condition
Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages. See all condition definitionsopens in a new window or tab
Seller Notes
“Some light wearing on cover. Inside pages clean. Very good condition”
ISBN
9780128008676
Category

About this product

Product Identifiers

Publisher
Elsevier Science & Technology
ISBN-10
0128008679
ISBN-13
9780128008676
eBay Product ID (ePID)
208699866

Product Key Features

Number of Pages
232 Pages
Publication Name
Social Sensing : Building Reliable Systems on Unreliable Data
Language
English
Publication Year
2015
Subject
Web / Social Media, Internet / General, Intelligence (Ai) & Semantics
Type
Textbook
Subject Area
Computers
Author
Dong Wang, Tarek Abdelzaher, Lance Kaplan
Format
Trade Paperback

Dimensions

Item Length
9.2 in
Item Width
7.5 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2015-297402
Reviews
"...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, Social Sensing, "...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
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
302.30285
Table Of Content
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
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, 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.
LC Classification Number
HM742

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