The Big Data paradigm presents many challenges for scientists from a range of disciplines. New research, tools, and technologies are currently being developed to harness the increasingly large quantities of data being generated within our society. This series aims to present new research and applications in Big Data, along with the computational tools and techniques currently in development. The goal of the series is to publish a broad range of textbooks, reference books, and handbooks that will:
The inclusion of concrete examples and applications is highly encouraged. The scope of the series includes, but is not limited to, titles in the areas of social networks, sensor networks, data-centric computing, astronomy, genomics, medical data analytics, large-scale e-commerce, and more. We are willing to consider other relevant topics proposed by potential contributors.
Frontiers in Data Science
Big Data Management and Processing
Big Data in Complex and Social Networks
Chengliang Yang, Chris Delcher, Elizabeth Shenkman, Sanjay Ranka
October 07, 2019
Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into...
Kuan-Ching Li, Beniamino Di Martino, Laurence T. Yang, Qingchen Zhang
March 13, 2019
Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data...
Arun K. Somani, Ganesh Chandra Deka
October 26, 2017
The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and...
October 10, 2017
High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, life...
Matthias Dehmer, Frank Emmert-Streib
October 09, 2017
Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation...
Kuan-Ching Li, Hai Jiang, Albert Y. Zomaya
May 25, 2017
From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and...
December 01, 2016
This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It...
My T. Thai, Weili Wu, Hui Xiong
November 08, 2016
This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the...
Matthias Dehmer, Frank Emmert-Streib, Stefan Pickl, Andreas Holzinger
August 18, 2016
Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an...
Kuan-Ching Li, Hai Jiang, Laurence T. Yang, Alfredo Cuzzocrea
February 23, 2015
As today’s organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly...