- Big data are datasets whose size is beyond the ability of commonly used algorithms and computing systems to capture, manage, and process the data within a reasonable time.
Big Data Mining and Analytics discovers hidden patterns, correlations, insights and knowledge through mining and analyzing large amounts of data obtained from various applications.
Big data come from many applications such as social media, sensors, Internet of Things, scientific applications, surveillance, video and image archives. With today’s technology in storage and computing and many newly invented statistical methods, data mining and machine learning algorithms such as deep learning, it is possible to analyze data and get good answers from them quickly.
Big Data Mining and Analytics addresses the most innovative developments, research issues and solutions in big data research and their applications.
Topics covered include:
Big Data theory, applications and challenges
Big Data mining and analytics on Cloud
Big Data Infrastructure, MapReduce and Cloud Computing
Big Data visualization
Big Data sharing, security, privacy and trust
Big Data placement, scheduling, and optimization
Big data for computer network traffic analyzing and security
Big data for large sensor networks
Big data for computational biology and bioinformatics
Big data for healthcare/medical applications
Big data for energy systems/smart grids
Big data for transportation systems
Big data for spatio-temporal systems
Big data for operational intelligence
Big Data for social networks
Big Data processing, resource scheduling and SLA on Cloud
Deep learning for Big Data
Large-scale workflow management in Big Data
Machine learning and pattern recognition of Big Data
Security, privacy, trust, risk in Big Data
Simulation and debugging of Big Data systems
Storage and computation management of Big Data
Volume, velocity, variety, value, and veracity of Big Data