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Crowdsourced data management = hybri...

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Crowdsourced data management = hybrid machine-human computing /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Crowdsourced data management/ by Guoliang Li ... [et al.].
其他題名:	hybrid machine-human computing /
其他作者:	Li, Guoliang.
出版者:	Singapore :Springer Singapore : : 2018.,
面頁冊數:	xii, 159 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Database management. -
電子資源:	https://doi.org/10.1007/978-981-10-7847-7
ISBN:	9789811078477

Crowdsourced data management = hybrid 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

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

557799
Database management.

LC Class. No.: QA76.9.D3

Dewey Class. No.: 005.74

Crowdsourced data management = hybrid machine-human computing /
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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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