Part I. Fundamentals
Large-Scale Clustering Algorithm
On High Dimensional Search Space and Learning Methods Enhanced Over_Sampling Techniques for Imbalanced Big Data Set Classification
Online Anomaly Detection in Big Data: The First Line of Defense Against Intruders
Developing Modified Classifier for Big Data Paradigm: An Approach through Bio-Inspired Soft Computing
Unified Framework for Control of Machine Learning Tasks Towards Effective and Efficient Processing of Big Data
An Efficient Approach for Mining High Utility Item sets over Data Streams
Event Detection in Location-Based Social Networks
Part II. Applications
Using Computational Intelligence for the Safety Assessment of Oil and Gas Pipelines: A Survey
Big Data for Effective Management of Smart Grids
Distributed Machine Learning on Smart-Gateway Network Towards Real-Time Indoor Data Analytics
Predicting Spatiotemporal Impacts of Weather on Power Systems using Big Data Science

This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business. Data science and big data go hand in hand and constitute a rapidly growing area of research and have Read more...