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  • © 2007

Data Streams

Models and Algorithms

  • Unique in its primary focus on data streams
  • Includes data streams that perform real-time fraud detection
  • Includes supplementary material: sn.pub/extras

Part of the book series: Advances in Database Systems (ADBS, volume 31)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xviii
  2. An Introduction to Data Streams

    • Charu C. Aggarwal
    Pages 1-8
  3. On Clustering Massive Data Streams: A Summarization Paradigm

    • Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu
    Pages 9-38
  4. A Survey of Classification Methods in Data Streams

    • Mohamed Medhat Gaber, Arkady Zaslavsky, Shonali Krishnaswamy
    Pages 39-59
  5. Frequent Pattern Mining in Data Streams

    • Ruoming Jin, Gagan Agrawal
    Pages 61-84
  6. Multi-Dimensional Analysis of Data Streams Using Stream Cubes

    • Jiawei Han, Y. Dora Cai, Yixin Chen, Guozhu Dong, Jian Pei, Benjamin W. Wah et al.
    Pages 103-125
  7. Load Shedding in Data Stream Systems

    • Brian Babcock, Mayur Datar, Rajeev Motwani
    Pages 127-147
  8. The Sliding-Window Computation Model and Results

    • Mayur Datar, Rajeev Motwani
    Pages 149-167
  9. A Survey of Synopsis Construction in Data Streams

    • Charu C. Aggarwal, Philip S. Yu
    Pages 169-207
  10. A Survey of Join Processing in Data Streams

    • Junyi Xie, Jun Yang
    Pages 209-236
  11. Indexing and Querying Data Streams

    • Ahmet Bulut, Ambuj K. Singh
    Pages 237-259
  12. Dimensionality Reduction and Forecasting on Streams

    • Spiros Papadimitriou, Jimeng Sun, Christos Faloutsos
    Pages 261-288
  13. A Survey of Distributed Mining of Data Streams

    • Srinivasan Parthasarathy, Amol Ghoting, Matthew Eric Otey
    Pages 289-307
  14. Algorithms for Distributed Data Stream Mining

    • Kanishka Bhaduri, Kamalika Das, Krishnamoorthy Sivakumar, Hillol Kargupta, Ran Wolff, Rong Chen
    Pages 309-331
  15. A Survey of Stream Processing Problems and Techniques in Sensor Networks

    • Sharmila Subramaniam, Dimitrios Gunopulos
    Pages 333-352
  16. Back Matter

    Pages 353-354

About this book

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.

 

Reviews

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)

Editors and Affiliations

  • IBM, Thomas J. Watson Research Center, Hawthorne

    Charu C. Aggarwal

About the editor

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.

Bibliographic Information

Buy it now

Buying options

eBook USD 89.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access