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Crowdsourced Data Management : Hybrid Machine-Human Computing - Guoliang Li

Crowdsourced Data Management

Hybrid Machine-Human Computing

By: Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin

eText | 12 October 2018

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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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Non-FictionComputing & I.T.Computer ScienceArtificial IntelligenceExpert Systems & Knowledge-Based SystemsDatabasesData MiningComputer Programming & Software DevelopmentMobile & Handheld Device Programming & Apps Programming

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Paperback

Published: 1st February 2019

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