Crowdsourced Data Management Hybrid Machine-Human Computing /

• Main Authors: Li, Guoliang (Author, http://id.loc.gov/vocabulary/relators/aut), Wang, Jiannan (http://id.loc.gov/vocabulary/relators/aut), Zheng, Yudian (http://id.loc.gov/vocabulary/relators/aut), Fan, Ju (http://id.loc.gov/vocabulary/relators/aut), Franklin, Michael J. (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Subjects: Big data.; Database management.; Special purpose computers.; Data mining.; Mobile computing.; Big Data.; Database Management.; Special Purpose and Application-Based Systems.; Data Mining and Knowledge Discovery.; Mobile Computing.

This book provides an overview of crowdsourced data management. Covering all aspects including the workflow, algorithms and research potential, it particularly focuses on the latest techniques and recent advances. The authors identify three key aspects in determining the performance of crowdsourced...

Table of Contents:

• 1. Introduction
• 2. Crowdsourcing Background. 3. Quality Control
• 4. Cost Control
• 5. Latency Control
• 6. Crowdsourcing Database Systems and Optimization
• 7. Crowdsourced Operators
• Conclusion.