Data Streams: Models and Algorithms (Advances in Database...

Features

• Cover Type: Hard Cover with 358 pages
• Published by: Springer
• Edition: 1st Edition November 27, 2006
• Written in: English
• ISBN 10 Number: 0387287590
• ISBN 13 Number: 978-0387287591
• Book Dimensions: 9.3 x 6.2 x 1 inches
• Weighs: 1.6 pounds

Product Review


From the reviews:

"This book is the very first attempt to record the challenges and present the solutions currently adopted to deal with the data streams. … All chapters are written by prominent researchers in the field … which makes the material in the book invaluable. This book is mainly intended for researchers, graduate students, and developers in industry. … This book will be very useful for researchers or practitioners in the field of data streams, despite the fast growth of this field. Overall, we highly recommend it." (Yannis Manolopoulos and Maria Kontaki, Computing Reviews, January, 2008)

Product Description


Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams.  Recent progress in hardware technology makes it possible for organizations to store and record large streams of transactional data. For example, even simple daily transactions such as using the credit card or phone result in automated data storage, which brings us to a fairly new topic called data streams.

This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions.

Data Streams: Models and Algorithms is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.

 



Reader Reviews
This book is about mining data streams (or data stream mining). Its title is not very accurate but if you see its TOC you will easily understand. It covers the main areas of data stream mining and is accurate and informative. Recommended if you are interested in data streams or data stream mining or mining data streams. PS. There are some small typos at the first thirty pages of the book.