Advanced Intelligent Systems for Sustainable Development (AI2SDâ2019)

This book contains papers presented at the Second Edition of the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD'2019), which was held in Marrakech, Morocco on 08-11 July 2019. This Volume offers comprehensive coverage of recent advancements in Big Data, Data analytics, and related paradigms. The volume consists of fifty-two chapters each chapter covers the most recent research in the field of big Data and Data science, describes use cases and applications of Big Data technologies within various domains such as social networks, healthcare, etc...

All parts of the volume discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains.This volume surveys the state of the art in data science, and provides practical guidance on big data analytics and data science. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics.

This volume designed for researchers, IT professionals and graduate students, this volume is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance, medicine and healthcare, and networks, Internet of Things, Big Data standards, bench-marking of systems, and others.

In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.