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Crowdsourced data managementhybrid m...

Li, Guoliang.

Crowdsourced data managementhybrid machine-human computing /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Crowdsourced data managementby Guoliang Li ... [et al.].
Reminder of title:	hybrid machine-human computing /
other author:	Li, Guoliang.
Published:	Singapore :Springer Singapore :2018.
Description:	xii, 159 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Database management.
Online resource:	https://doi.org/10.1007/978-981-10-7847-7
ISBN:	9789811078477$q(electronic bk.)

Crowdsourced data managementhybrid machine-human computing /
Crowdsourced data managementhybrid machine-human computing /[electronic resource] :by Guoliang Li ... [et al.]. - Singapore :Springer Singapore :2018. - xii, 159 p. :ill., digital ;24 cm.

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

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.

ISBN: 9789811078477$q(electronic bk.)

Standard No.: 10.1007/978-981-10-7847-7doiSubjects--Topical Terms:

182428
Database management.

LC Class. No.: QA76.9.D3

Dewey Class. No.: 005.74

Crowdsourced data managementhybrid machine-human computing /
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245 0 0 $a Crowdsourced data management $h [electronic resource] : $b hybrid machine-human computing / $c by Guoliang Li ... [et al.].
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505 0 $a 1. Introduction -- 2. Crowdsourcing Background. 3. Quality Control -- 4. Cost Control -- 5. Latency Control -- 6. Crowdsourcing Database Systems and Optimization -- 7. Crowdsourced Operators -- Conclusion.
520 $a 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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