Big Data Concepts, Theories, and Applications

This book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directions for Big Data in research and practice. It also focuses on high level concepts such as definitions of Big Data from different angles; surveys in research and applications; and existing tools, mechanisms, and systems in practice. Each chapter is independent from the other chapters, allowing users to read any chapter directly. After examining the practical side of Big Data, this book presents theoretical perspectives. The theoretical research ranges from Big Data representation, modeling and topology to distribution and dimension reducing. Chapters also investigate the many disciplines that involve Big Data, such as statistics, data mining, machine learning, networking, algorithms, security and differential geometry. The last section of this book introduces Big Data applications from different communities, such as business, engineering and science. __Big Data Concepts, Theories and Applications__ is designed as a reference for researchers and advanced level students in computer science, electrical engineering and mathematics. Practitioners who focus on information systems, big data, data mining, business analysis and other related fields will also find this material valuable. This Book Covers Three Major Parts Of Big Data: Concepts, Theories And Applications. Written By World-renowned Leaders In Big Data, This Book Explores The Problems, Possible Solutions And Directions For Big Data In Research And Practice. It Also Focuses On High Level Concepts Such As Definitions Of Big Data From Different Angles; Surveys In Research And Applications; And Existing Tools, Mechanisms, And Systems In Practice. Each Chapter Is Independent From The Other Chapters, Allowing Users To Read Any Chapter Directly. After Examining The Practical Side Of Big Data, This Book Presents Theoretical Perspectives. The Theoretical Research Ranges From Big Data Representation, Modeling And Topology To Distribution And Dimension Reducing. Chapters Also Investigate The Many Disciplines That Involve Big Data, Such As Statistics, Data Mining, Machine Learning, Networking, Algorithms, Security And Differential Geometry. The Last Section Of This Book Introduces Big Data Applications From Different Communities, Such As Business, Engineering And Science. Big Data Concepts, Theories And Applications Is Designed As A Reference For Researchers And Advanced Level Students In Computer Science, Electrical Engineering And Mathematics. Practitioners Who Focus On Information Systems, Big Data, Data Mining, Business Analysis And Other Related Fields Will Also Find This Material Valuable. . Big Continuous Data: Dealing With Velocity By Composing Event Streams -- Big Data Tools And Platforms -- Traffic Identification In Big Internet Data -- Security Theories And Practices For Big Data -- Rapid Screening Of Big Data Against Inadvertent Leaks -- Big Data Storage Security -- Cyber Attacks On Mapreduce Computation Time In A Hadoop Cluster -- Security And Privacy For Big Data -- Big Data Applications In Engineering And Sciences -- Geospatial Big Data For Environmental And Agricultural Applications -- Big Data In Finance -- Big Data Applications In Business Analytics. Edited By Shui Yu, Song Guo. Front Matter....Pages i-viii Big Continuous Data: Dealing with Velocity by Composing Event Streams....Pages 1-27 Big Data Tools and Platforms....Pages 29-128 Traffic Identification in Big Internet Data....Pages 129-156 Security Theories and Practices for Big Data....Pages 157-192 Rapid Screening of Big Data Against Inadvertent Leaks....Pages 193-235 Big Data Storage Security....Pages 237-255 Cyber Attacks on MapReduce Computation Time in a Hadoop Cluster....Pages 257-279 Security and Privacy for Big Data....Pages 281-313 Big Data Applications in Engineering and Science....Pages 315-351 Geospatial Big Data for Environmental and Agricultural Applications....Pages 353-390 Big Data in Finance....Pages 391-412 Big Data Applications in Business Analysis....Pages 413-437