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Big Data and Visual Analytics 1st ed. 2017 [Hardback]

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  • Formāts: Hardback, 263 pages, height x width: 235x155 mm, weight: 582 g, 10 Illustrations, color; 17 Illustrations, black and white; X, 263 p. 27 illus., 10 illus. in color., 1 Hardback
  • Izdošanas datums: 17-Jan-2018
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319639153
  • ISBN-13: 9783319639154
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  • Hardback
  • Cena: 127,23 €*
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  • Formāts: Hardback, 263 pages, height x width: 235x155 mm, weight: 582 g, 10 Illustrations, color; 17 Illustrations, black and white; X, 263 p. 27 illus., 10 illus. in color., 1 Hardback
  • Izdošanas datums: 17-Jan-2018
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319639153
  • ISBN-13: 9783319639154
Citas grāmatas par šo tēmu:

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.

Automated Detection of Central Retinal Vein Occlusion Using Convolutional Neural Network
1(22)
Bismita Choudhury
Patrick H.H. Then
Valliappan Raman
Swarm Intelligence Applied to Big Data Analytics for Rescue Operations with RASEN Sensor Networks
23(32)
U. John Tanik
Yuehua Wang
Serkan Guldal
Gender Classification Based on Deep Learning
55(16)
Dhiraj Gharana
Sang C. Suh
Mingon Kang
Social and Organizational Culture in Korea and Women's Career Development
71(14)
Choonhee Yang
Yongman Kwon
Big Data Framework for Agile Business (BDFAB) As a Basis for Developing Holistic Strategies in Big Data Adoption
85(12)
Bhuvan Unhelkar
Scalable Gene Sequence Analysis on Spark
97(18)
Muthahar Syed
Taehyun Hwang
Jinoh Kim
Big Sensor Data Acquisition and Archiving with Compression
115(30)
Dongeun Lee
Advanced High Performance Computing for Big Data Local Visual Meaning
145(20)
Ozgur Aksu
Transdisciplinary Benefits of Convergence in Big Data Analytics
165(16)
U. John Tanik
Darrell Fielder
A Big Data Analytics Approach in Medical Imaging Segmentation Using Deep Convolutional Neural Networks
181(10)
Zheng Zhang
David Odaibo
Frank M. Skidmore
Murat M. Tanik
Big Data in Libraries
191(12)
Robert Olendorf
Yan Wang
A Framework for Social Network Sentiment Analysis Using Big Data Analytics
203(16)
Bharat Sri Harsha Karpurapu
Leon Jololian
Big Data Analytics and Visualization: Finance
219(12)
Shyam Prabhakar
Larry Maves
Study of Hardware Trojans in a Closed Loop Control System for an Internet-of-Things Application
231(14)
Ranveer Kumar
Karthikeyan Lingasubramanian
High Performance/Throughput Computing Workflow for a Neuro-Imaging Application: Provenance and Approaches
245(12)
T. Anthony
J.P. Robinson
J.R. Marstrander
G.R. Brook
M. Horton
F.M. Skidmore
Index 257