Big Data Technologies and Applications Front Cover

Big Data Technologies and Applications

  • Length: 400 pages
  • Edition: 1st ed. 2016
  • Publisher:
  • Publication Date: 2016-09-17
  • ISBN-10: 3319445480
  • ISBN-13: 9783319445489
  • Sales Rank: #5987948 (See Top 100 Books)
Description

The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform.

The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification.

The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.

Table of Contents

Chapter 1 Introduction to Big Data
Chapter 2 Big Data Analytics
Chapter 3 Transfer Learning Techniques
Chapter 4 Visualizing Big Data
Chapter 5 Deep Learning Techniques in Big Data Analytics
Chapter LexisNexis Risk Solution to Big Data
Chapter 6 The HPCC/ECL Platform for Big Data
Chapter 7 Scalable Automated Linking Technology for Big Data Computing
Chapter 8 Aggregated Data Analysis in HPCC Systems
Chapter 9 Models for Big Data
Chapter 10 Data Intensive Supercomputing Solutions
Chapter 11 Graph Processing with Massive Datasets: A Kel Primer
Chapter Big Data Applications
Chapter 12 HPCC Systems for Cyber Security Analytics
Chapter 13 Social Network Analytics: Hidden and Complex Fraud Schemes
Chapter 14 Modeling Ebola Spread and Using HPCC/KEL System
Chapter 15 Unsupervised Learning and Image Classification in High Performance Computing Cluster

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