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Guide to Big Data Applications

  • S. Srinivasan

Part of the Studies in Big Data book series (SBD, volume 26)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. General

    1. Front Matter
      Pages 1-1
    2. Joe Weinman
      Pages 3-27
    3. Ann Cavoukian, Michelle Chibba
      Pages 29-48
    4. Wenrui Dai, Shuang Wang, Hongkai Xiong, Xiaoqian Jiang
      Pages 49-82
  3. Applications in Science

    1. Front Matter
      Pages 105-105
    2. Hongmei Chi, Sharmini Pitter, Nan Li, Haiyan Tian
      Pages 107-124
    3. Rishi Divate, Sankalp Sah, Manish Singh
      Pages 125-147
    4. Jiefu Chen, Yueqin Huang, Tommy L. Binford Jr., Xuqing Wu
      Pages 149-173
    5. Mark Kerzner, Pierre Jean Daniel
      Pages 175-204
    6. Shankar Iyer
      Pages 205-244
    7. Fatema Rashid, Ali Miri
      Pages 245-271
    8. Yu Liang, Dalei Wu, Dryver Huston, Guirong Liu, Yaohang Li, Cuilan Gao et al.
      Pages 295-325
  4. Applications in Medicine

    1. Front Matter
      Pages 327-327
    2. Ashfaque Shafique, Mohamed Sayeed, Konstantinos Tsakalis
      Pages 329-369
    3. Pankush Kalgotra, Ramesh Sharda, Bhargav Molaka, Samsheel Kathuri
      Pages 401-413
    4. Elizabeth Le, Sowmya Iyer, Teja Patil, Ron Li, Jonathan H. Chen, Michael Wang et al.
      Pages 415-448
  5. Applications in Business

    1. Front Matter
      Pages 449-449
    2. Rimvydas Skyrius, Gintarė Giriūnienė, Igor Katin, Michail Kazimianec, Raimundas Žilinskas
      Pages 451-486
    3. S. Srinivasan
      Pages 487-502
  6. Back Matter
    Pages 523-565

About this book

Introduction

This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics,   biology, energy, healthcare, and   business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.

Keywords

Big Data Analytics Big Data And Social Media Cloud Computing For Big Data In Business Multidisciplinary Big Data High Performance Computing And Big Data Privacy Implications Of Big Data Legal Perspectives Of Big Data

Editors and affiliations

  • S. Srinivasan
    • 1
  1. 1.Jesse H. Jones School of BusinessTexas Southern University HoustonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-53817-4
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-53816-7
  • Online ISBN 978-3-319-53817-4
  • Series Print ISSN 2197-6503
  • Series Online ISSN 2197-6511
  • Buy this book on publisher's site