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Big Data and Visual Analytics / edited by Sang C. Suh, Thomas Anthony.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Suh, Sang C., editor.
Anthony, Thomas (Civil engineer), editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Language:
English
Subjects (All):
Computers.
Artificial intelligence.
Mathematics.
Visualization.
Information Systems and Communication Service.
Artificial Intelligence.
Local Subjects:
Information Systems and Communication Service.
Artificial Intelligence.
Visualization.
Physical Description:
1 online resource (X, 263 pages) : 27 illustrations, 10 illustrations in color
Edition:
First edition 2017.
Contained In:
Springer eBooks
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2017.
System Details:
text file PDF
Summary:
This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.
Contents:
Information visualization
Data analytics
Visual analytics
Intelligent information systems
Business analytics,- Virtual data machine
Big data architecture
Security of big data
Big data applications
Tensor-based computation and modeling
High performance computing cluster
Big data technologies.
Other Format:
Printed edition:
ISBN:
978-3-319-63917-8
9783319639178
Access Restriction:
Restricted for use by site license.

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