Big data technologies and applications : 7th International Conference, BDTA 2016, Seoul, South Korea, November 17-18, 2016, Proceedings

The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform.The book comprises 15 chapters broken into three parts. The first part, __Big Data Technologies__, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, __LexisNexis Risk Solution to Big Data__, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, __Big Data Applications__, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification.The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors. The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies , includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data , focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications , describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors. Front Matter....Pages i-xviii Front Matter....Pages 1-1 Introduction to Big Data....Pages 3-11 Big Data Analytics....Pages 13-52 Transfer Learning Techniques....Pages 53-99 Visualizing Big Data....Pages 101-131 Deep Learning Techniques in Big Data Analytics....Pages 133-156 Front Matter....Pages 157-157 The HPCC/ECL Platform for Big Data....Pages 159-183 Scalable Automated Linking Technology for Big Data Computing....Pages 185-223 Aggregated Data Analysis in HPCC Systems....Pages 225-235 Models for Big Data....Pages 237-255 Data Intensive Supercomputing Solutions....Pages 257-306 Graph Processing with Massive Datasets: A Kel Primer....Pages 307-328 Front Matter....Pages 329-329 HPCC Systems for Cyber Security Analytics....Pages 331-339 Social Network Analytics: Hidden and Complex Fraud Schemes....Pages 341-346 Modeling Ebola Spread and Using HPCC/KEL System....Pages 347-385 Unsupervised Learning and Image Classification in High Performance Computing Cluster....Pages 387-400