Big Data Mining

The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016.

This book presents basic concepts, ideas, and research in data mining.

This book on data mining explores a broad set of ideas and presents some of the state-of-the-art research in this field. The book is triggered by pervasive applications that retrieve knowledge from real-world big data. The intended audience of this book will mainly consist of researchers, research students, practitioners, data analysts, and business professionals who seek information on the various data mining techniques and their 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.

The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation?