Handbook of Big Data Analytics: Methodologies

This comprehensive edited 2-volume handbook presents a large spectrum of contributions on methodologies and applications of Big Data Analytics. In the first volume and using frameworks such as Hadoop MapReduce, Apache Spark and GPGPU programming, the authors cover methodologies including association rule mining, regression, recommender systems, text analytics, data lakes, data Cataloguing, in-memory databases, indexing approaches, data partitioning strategies, scalable search architectures, machine learning algorithms. In the second volume, the authors cover a wide range of applications including security, fraud detection, Internet & dark web data analytics, IoT & cyber physical systems, customer churn prediction, behaviour analytics, business Analytics and more.