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Social sensing : building reliable systems on unreliable data /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Waltham, MA :
Morgan Kaufmann,
[2015]
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| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Wang, Dong, |e author. | |
| 245 | 1 | 0 | |a Social sensing : |b building reliable systems on unreliable data / |c Dong Wang, Tarek Abdelzaher, Lance Kaplan. |
| 246 | 3 | 0 | |a Building reliable systems on unreliable data |
| 250 | |a First edition. | ||
| 264 | 1 | |a Waltham, MA : |b Morgan Kaufmann, |c [2015] | |
| 264 | 4 | |c �2015 | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Online resource; title from title page (Safari, viewed May 8, 2015). | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a 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. | ||
| 505 | 0 | |a Front Cover; Front Cover; Social Sensing: Building Reliable Systems on Unreliable Data; Copyright; Dedication; Contents; Acknowledgments; Authors; Dong Wang; Tarek Abdelzaher; Lance M. Kaplan; Foreword; Preface; Chapter 1: A new information age; 1.1 Overview; 1.2 Challenges; 1.3 State of the Art; 1.3.1 Efforts on Discount Fusion; 1.3.2 Efforts on Trust and Reputation Systems; 1.3.3 Efforts on Fact-Finding; 1.4 Organization; Chapter 2: Social Sensing Trends and Applications; 2.1 Information Sharing: The Paradigm Shift; 2.2 An Application Taxonomy; 2.3 Early Research; 2.4 The Present Time. | |
| 505 | 8 | |a 2.5 ANote on PrivacyChapter 3: Mathematical foundations of social sensing: An introductory tutorial; 3.1 AMultidisciplinary Background; 3.2 Basics of Generic Networks; 3.3 Basics of Bayesian Analysis; 3.4 Basics of Maximum Likelihood Estimation; 3.5 Basics of Expectation Maximization; 3.6 Basics of Confidence Intervals; 3.7 Putting It All Together; Chapter 4: Fact-finding in information networks; 4.1 Facts, Fact-Finders, and the Existence of Ground Truth; 4.2 Overview of Fact-Finders in Information Networks; 4.3 A Bayesian Interpretation of Basic Fact-Finding; 4.3.1 Claim Credibility. | |
| 505 | 8 | |a 4.3.2 Source Credibility4.4 The Iterative Algorithm; 4.5 Examples and Results; 4.6 Discussion; Appendix; Chapter 5: Social Sensing: A maximum likelihood estimation approach; 5.1 The Social Sensing Problem; 5.2 Expectation Maximization; 5.2.1 Background; 5.2.2 Mathematical Formulation; 5.2.3 Deriving the E-Step and M-Step; 5.3 The EM Fact-Finding Algorithm; 5.4 Examples and Results; 5.4.1 A Simulation Study; 5.4.2 A Geotagging Case Study; 5.4.3 A Real World Application; 5.5 Discussion; Chapter 6: Confidence bounds in social sensing; 6.1 The Reliability Assurance Problem. | |
| 505 | 8 | |a 6.2 Actual Cramer-Rao Lower Bound6.3 Asymptotic Cramer-Rao Lower Bound; 6.4 Confidence Interval Derivation; 6.5 Examples and Results; 6.5.1 Evaluation of Confidence Interval; 6.5.2 Evaluation of CRLB; Scalability study; Trustworthiness and assertiveness study; Robustness study; 6.5.3 Evaluation of Estimated False Positives/Negatives on Claim Classification; Scalability study; Trustworthiness and assertiveness study; Robustness study; 6.5.4 AReal World Case Study; 6.6 Discussion; Appendix; Chapter 7: Resolving conflicting observations and non-binary claims. | |
| 505 | 8 | |a 7.1 Handling Conflicting Binary Observations7.1.1 Extended Model; 7.1.2 Re-Derive the E-Step and M-Step; 7.1.3 The Binary Conflict EM Algorithm; 7.2 Handling Non-Binary Claims; 7.2.1 Generalized E and M Steps for Non-Binary Measured Variables; 7.2.2 The Generalized EM Algorithm for Non-Binary Measured Variables; 7.3 Performance Evaluation; 7.3.1 AReal World Application; 7.3.2 ASimulation Study for Conflicting Observations; 7.3.3 ASimulation Study for Non-Binary Claims; 7.4 Discussion; Appendix; Chapter 8: Understanding the social network; 8.1 Information Propagation Cascades. | |
| 650 | 0 | |a Social media. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Big data. | |
| 650 | 6 | |a M�edias sociaux. |0 (CaQQLa)000258927 | |
| 650 | 6 | |a Exploration de donn�ees (Informatique) |0 (CaQQLa)201-0300292 | |
| 650 | 6 | |a Donn�ees volumineuses. |0 (CaQQLa)000284673 | |
| 650 | 7 | |a social media. |2 aat |0 (CStmoGRI)aat300312269 | |
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| 650 | 7 | |a COMPUTERS |x Data Processing. |2 bisacsh | |
| 650 | 7 | |a COMPUTERS |x Hardware |x General. |2 bisacsh | |
| 650 | 7 | |a COMPUTERS |x Information Technology. |2 bisacsh | |
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| 650 | 7 | |a Social media |2 fast |0 (OCoLC)fst01741098 | |
| 700 | 1 | |a Abdelzaher, Tarek, |e author. | |
| 700 | 1 | |a Kaplan, Lance, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Wang, Dong. |t Social Sensing : Building Reliable Systems on Unreliable Data. |d Burlington : Elsevier Science, �2015 |z 9780128008676 |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780128008676 |z Texto completo |