Big Data Technologies and Applications

  • Borko Furht
  • Flavio Villanustre

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Big Data Technologies

    1. Front Matter
      Pages 1-1
    2. Borko Furht, Flavio Villanustre
      Pages 3-11
    3. Chun-Wei Tsai, Chin-Feng Lai, Han-Chieh Chao, Athanasios V. Vasilakos
      Pages 13-52
    4. Karl Weiss, Taghi M. Khoshgoftaar, DingDing Wang
      Pages 53-99
    5. Ekaterina Olshannikova, Aleksandr Ometov, Yevgeni Koucheryavy, Thomas Olsson
      Pages 101-131
    6. Maryam M. Najafabadi, Flavio Villanustre, Taghi M. Khoshgoftaar, Naeem Seliya, Randall Wald, Edin Muharemagc
      Pages 133-156
  3. LexisNexis Risk Solution to Big Data

    1. Front Matter
      Pages 157-157
    2. Anthony M. Middleton, David Alan Bayliss, Gavin Halliday, Arjuna Chala, Borko Furht
      Pages 159-183
    3. Anthony M. Middleton, David Bayliss, Bob Foreman
      Pages 185-223
    4. David Bayliss
      Pages 225-235
    5. David Bayliss
      Pages 237-255
    6. Anthony M. Middleton
      Pages 257-306
    7. David Bayliss, Flavio Villanustre
      Pages 307-328
  4. Big Data Applications

    1. Front Matter
      Pages 329-329
    2. Flavio Villanustre, Mauricio Renzi
      Pages 331-339
    3. Flavio Villanustre, Borko Furht
      Pages 341-346
    4. Jesse Shaw, Flavio Villanustre, Borko Furht, Ankur Agarwal, Abhishek Jain
      Pages 347-385
    5. I. Itauma, M. S. Aslan, X. W. Chen, Flavio Villanustre
      Pages 387-400

About this book


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. 


Big data technologies Big data applications HPCC systems Big data analytics Big data components Visualization of big data Models of big data Social network analytics ECL language Big data software Machine learning techniques Deep learning techniques Data security and privacy Data intensive supercomputing

Authors and affiliations

  • Borko Furht
    • 1
  • Flavio Villanustre
    • 2
  1. 1.Department of Computer Science and EngineeringFlorida Atlantic UniversityBoca RatonUSA
  2. 2.LexisNexis Risk SolutionsAlpharettaUSA

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-44548-9
  • Online ISBN 978-3-319-44550-2
  • Buy this book on publisher's site