Springer, 2016. — 439 p. — ISBN: 3319277618, 9783319277615This 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.

Springer, 2016. - 439页 - ISBN: 3319277618, 9783319277615本书涵盖大数据的三个主要部分：概念、理论和应用。本书由世界知名的大数据领域领导人撰写，探讨了大数据在研究和实践中的问题、可能的解决方案和方向。本书还关注高层次的概念，如从不同角度对大数据的定义；研究和应用中的调查；以及实践中的现有工具、机制和系统。每一章都独立于其他章节，允许用户直接阅读任何章节。

在研究了大数据的实践方面后，本书提出了理论观点。理论研究的范围从大数据的表示、建模和拓扑学到分布和降维。各章还研究了涉及大数据的许多学科，如统计学、数据挖掘、机器学习、网络、算法、安全和微分几何。本书的最后一节介绍了来自不同社区的大数据应用，如商业、工程和科学。

大数据概念、理论和应用》旨在为计算机科学、电气工程和数学领域的研究人员和高层次学生提供参考。专注于信息系统、大数据、数据挖掘、商业分析和其他相关领域的从业人员也会发现这些材料的价值。