Description 
1 online resource (xiv, 180 pages) 

text txt rdacontent 

computer c rdamedia 

online resource cr rdacarrier 

text file PDF rda 
Bibliography 
Includes bibliographical references and index. 
Note 
Online resource; title from PDF title page (EBSCO, viewed June 13, 2018). 
Contents 
Intro; Table of Contents; About the Author; Acknowledgments; Introduction; Chapter 1: The Big Data Phenomenon; Why "Big" Data; The V's of Big Data; Veracity  The Fourth 'V'; Summary; Chapter 2: Veracity of Web Information; The Problem; The Causes; The Effects; The Remedies; Characteristics of a Trusted Website; Summary; Chapter 3: Approaches to Establishing Veracity of Big Data; Machine Learning; Change Detection; Optimization Techniques; Natural Language Processing; Formal Methods; Fuzzy Logic; Information Retrieval Techniques; Blockchain; Summary; Chapter 4: Change Detection Techniques. 

Sequential Probability Ratio Test (SPRT)The CUSUM Technique; Kalman Filter; Summary; Chapter 5: Machine Learning Algorithms; The Microblogging Example; Collecting the Ground Truth; Logistic Regression; Naïve Bayes Classifier; Support Vector Machine; Artificial Neural Networks; KMeans Clustering; Summary; Chapter 6: Formal Methods; Terminology; Propositional Logic; Predicate Calculus; Fuzzy Logic; Summary; Chapter 7: Medley of More Methods; Collaborative Filtering; Vector Space Model; Summary; Chapter 8: The Future: Blockchain and Beyond; Blockchain Explained; Blockchain for Big Data Veracity. 
Summary 
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 easytounderstand language. Determining the truth of big data in realworld 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 Twitter have 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 easytounderstand language and examples Use diverse tools and techniques such as machine learning algorithms, Blockchain, and the Kalman filter to address veracity issues. 
Subject 
Verification (Logic)  Computer programs.


Computer algorithms.


Databases  Evaluation.


Data editing.


Data integrity.


COMPUTERS  General.


Computer algorithms. (OCoLC)fst00872010


Data editing. (OCoLC)fst00887933


Data integrity. (OCoLC)fst01746571


Databases  Evaluation. (OCoLC)fst00888069


Computer Science.


Big Data.


Computing Methodologies.


Artificial intelligence.


Databases.

Genre/Form 
Electronic books.


Electronic books.

Other Form: 
Print version: Pendyala, Vishnu. Veracity of big data. [United States] : Apress, [2018] 1484236327 9781484236321 (OCoLC)1028953663 
ISBN 
9781484236338 (electronic bk.) 

1484236335 (electronic bk.) 

1484236327 

9781484236321 

9781484236321 

1484236327 
Standard No. 
10.1007/9781484236338 doi 

9781484236321 

GBVCP 1029873089 

UKMGB 019183857 
