Exploring how to extract knowledge structures from evolving and time-changing data, this book presents a coherent overview of state-of-the-art research in learning from data streams. It covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, and customer click streams. It also explores advanced areas, such as ubiquitous data stream mining; addresses several challenges of data mining in the future, when stream mining will be at the core of many applications; and includes pseudo-code of more than 30 streaming-like algorithms.
• Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
Algorithms & Complexity
Data Preparation & Mining
Machine Learning
Reference

Addressing the issues challenging the sensor community, this book presents innovative solutions in offline data mining and real-time analysis of sensor or geographically distributed data. Illustrated with case studies, it discusses the challenges and requirements for sensor data-based knowledge discovery solutions in high-priority application. The book then explores the fusion between heterogeneous data streams from multiple sensor types and applications in science, engineering, and security. Bringing together researchers from academia, government, and the private sector, this book delineates the application of knowledge modeling in data intensive operations.
• Industrial Innovation
Data Preparation & Mining
Operations Research
Reference
Professional