Crowdsourced Data Management

Hybrid Machine-Human Computing

Nonfiction, Computers, Advanced Computing, Programming, Expert Systems, Database Management, General Computing
Cover of the book Crowdsourced Data Management by Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin, Springer Singapore
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Author: Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin ISBN: 9789811078477
Publisher: Springer Singapore Publication: October 12, 2018
Imprint: Springer Language: English
Author: Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin
ISBN: 9789811078477
Publisher: Springer Singapore
Publication: October 12, 2018
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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