Knowledge Discovery from Data Streams

By: Joao Gama

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Hardcover | 4 June 2010 | Edition Number 1

At a Glance

Hardcover
258 Pages

Dimensions(cm)
23.39 x 15.6 x 1.6

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$333.99

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Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams.

The book 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 addresses several challenges of data mining in the future, when stream mining will be at the core of many applications. These challenges involve designing useful and efficient data mining solutions applicable to real-world problems. In the appendix, the author includes examples of publicly available software and online data sets.

This practical, up-to-date book focuses on the new requirements of the next generation of data mining. Although the concepts presented in the text are mainly about data streams, they also are valid for different areas of machine learning and data mining.

Industry Reviews

"!Gama is one of the leading investigators in the hottest research topic in machine learning and data mining: data streams. ! This book is the first book to didactically cover in a clear, comprehensive and mathematically rigorous way the main machine learning related aspects of this relevant research field. ! an up-to-date, broad and useful source of reference for all those interested in knowledge acquisition by learning techniques." --From the Foreword by Andre Ponce de Leon Ferreira de Carvalho, University of Sao Paulo, Brazil

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