Title: Data Streams: Models and Algorithms (Advances in Database Systems, 31)
Publisher: Springer
Publication Date: 2014
Language: English
ISBN 10: 146149768X
ISBN 13: 9781461497684
Binding: Soft cover
Condition: New

About this title

Synopsis

This book discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. 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. The book 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.

About the Author

Charu C. Aggarwal obtained his B.Tech in Computer Science from IIT Kanpur in 1993 and Ph.D. from MIT in 1996. He has been a Research Staff Member at IBM since then, and has published over 90 papers in major conferences and journals in the database and data mining field. He has applied for or been granted over 50 US and International patents, and has twice been designated Master Inventor at IBM for the commercial value of his patents. He has been granted 14 invention achievement awards by IBM for his patents. His work on real time bio-terrorist threat detection in data streams won the IBM Epispire award for environmental excellence in 2003. He has served on the program committee of most major database conferences, and was program chair for the Data Mining and Knowledge Discovery Workshop, 2003, and a program vice-chair for the SIAM Conference on Data Mining, 2007. He is an associate editor of the IEEE Transactions on Data Engineering and an action editor of the Data Mining and Knowledge Discovery Journal. He is a senior member of the IEEE.

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