Crowdsourced Data Management : Hybrid Machine-Human 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 data management: quality control, cost control and latency control. By surveying and synthesizing a wide spectrum of studies on crowdsourced data management, the book outlines important factors that need to be considered to improve crowdsourced data management. It also introduces a practical crowdsourced-database-system design and presents a number of crowdsourced operators. Self-contained and covering theory, algorithms, techniques and applications, it is a valuable reference resource for researchers and students new to crowdsourced data management with a basic knowledge of data structures and databases. Front Matter ....Pages i-xii Introduction (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 1-10 Crowdsourcing Background (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 11-20 Quality Control (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 21-44 Cost Control (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 45-62 Latency Control (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 63-70 Crowdsourcing Database Systems and Optimization (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 71-95 Crowdsourced Operators (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 97-154 Conclusion (Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin)....Pages 155-158 Back Matter ....Pages 159-159