Data Science and Big Data Computing - Frameworks and Methodologies (Hardcover, 1st ed. 2016)

This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	July 2016
First published:	2016
Editors:	Zaigham Mahmood
Dimensions:	235 x 155 x 25mm (L x W x T)
Format:	Hardcover - Cloth over boards
Pages:	319
Edition:	1st ed. 2016
ISBN-13:	978-3-319-31859-2
Categories:	Books > Computing & IT > Internet > Network computers Books > Computing & IT > Applications of computing > Databases > Data mining Promotions
LSN:	3-319-31859-4
Barcode:	9783319318592

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