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Veracity of Big Data

Machine Learning and Other Approaches to Verifying Truthfulness

  • Book
  • © 2018

Overview

Authors:
  1. Vishnu Pendyala

    1. San Jose, USA

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  • Presents solutions to a problem that is intimidatingly complex, increasingly important, and largely unsolved
  • Provides simple, easy-to-understand explanations of profound mathematical concepts
  • Includes an appropriate mix of theory and practice to present practical and interesting approaches
  • Opens the conversation on niche solutions that can play a significant role in the evolution of the research into big data veracity

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiv
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  2. The Big Data Phenomenon

    • Vishnu Pendyala
    Pages 1-15

  3. Veracity of Web Information

    • Vishnu Pendyala
    Pages 17-33

  4. Approaches to Establishing Veracity of Big Data

    • Vishnu Pendyala
    Pages 35-63

  5. Change Detection Techniques

    • Vishnu Pendyala
    Pages 65-86

  6. Machine Learning Algorithms

    • Vishnu Pendyala
    Pages 87-118

  7. Formal Methods

    • Vishnu Pendyala
    Pages 119-144

  8. Medley of More Methods

    • Vishnu Pendyala
    Pages 145-154

  9. The Future: Blockchain and Beyond

    • Vishnu Pendyala
    Pages 155-169

  10. Back Matter

    Pages 171-180
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Keywords

About this book

Examine the problem of maintaining the quality of big data and discover novel solutions. You will learn the four V’s of big data, including veracity, and study the problem from various angles. The solutions discussed are drawn from diverse areas of engineering and math, including machine learning, statistics, formal methods, and the Blockchain technology. 


Veracity of Big Data serves as an introduction to machine learning algorithms and diverse techniques such as the Kalman filter, SPRT, CUSUM, fuzzy logic, and Blockchain, showing how they can be used to solve problems in the veracity domain. Using examples, the math behind the techniques is explained in easy-to-understand language.



Determining the truth of big data in real-world applications involves using various tools to analyze the available information. This book delves into some of the techniques that can be used. Microblogging websites such as Twitterhave played a major role in public life, including during presidential elections. The book uses examples of microblogs posted on a particular topic to demonstrate how veracity can be examined and established. Some of the techniques are described in the context of detecting veiled attacks on microblogging websites to influence public opinion.


What You'll Learn
  • Understand the problem concerning data veracity and its ramifications
  • Develop the mathematical foundation needed to help minimize the impact of the problem using easy-to-understand language and examples
  • Use diverse tools and techniques such as machine learning algorithms, Blockchain, and the Kalman filter to address veracity issues


Who This Book Is For



Software developers and practitioners, practicing engineers, curious managers, graduate students, and research scholars



Authors and Affiliations

  • San Jose, USA

    Vishnu Pendyala

About the author

Vishnu Pendyala is a Senior Member of IEEE and of the Computer Society of India (CSI), with over two decades of software experience with industry leaders such as Cisco, Synopsys, Informix (now IBM), and Electronics Corporation of India Limited. He is on the executive council of CSI, a member of the Special Interest Group on Big Data Analytics, and is the founding editor of its flagship publication, Visleshana. He recently taught a short-term course on “Big Data Analytics for Humanitarian Causes,” which was sponsored by the Ministry of Human Resources, Government of India under the GIAN scheme, and he delivered multiple keynote presentations at IEEE-sponsored international conferences. Vishnu has been living and working in the Silicon Valley for over two decades.

Bibliographic Information

  • Book Title: Veracity of Big Data

  • Book Subtitle: Machine Learning and Other Approaches to Verifying Truthfulness

  • Authors: Vishnu Pendyala

  • DOI: https://doi.org/10.1007/978-1-4842-3633-8

  • Publisher: Apress Berkeley, CA

  • eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)

  • Copyright Information: Vishnu Pendyala 2018

  • Softcover ISBN: 978-1-4842-3632-1Published: 10 June 2018

  • eBook ISBN: 978-1-4842-3633-8Published: 08 June 2018

  • Edition Number: 1

  • Number of Pages: XIV, 180

  • Number of Illustrations: 41 b/w illustrations

  • Topics: Big Data, Artificial Intelligence

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