Crowdsourced Data Management - Hybrid Machine-Human Computing (Paperback, Softcover reprint of the original 1st ed. 2018)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	February 2019
First published:	2018
Authors:	Guoliang Li • Jiannan Wang • Yudian Zheng • Ju Fan • Michael J. Franklin
Dimensions:	235 x 155 x 9mm (L x W x T)
Format:	Paperback
Pages:	159
Edition:	Softcover reprint of the original 1st ed. 2018
ISBN-13:	978-981-13-4012-3
Categories:	Books > Computing & IT > Computer hardware & operating systems > Handheld devices (eg Palm, PocketPC) Books > Computing & IT > Computer programming > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
LSN:	981-13-4012-9
Barcode:	9789811340123

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