Data Streams

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.

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)

• An Introduction to Data Streams.- On Clustering Massive Data Streams: A Summarization Paradigm.- A Survey of Classification Methods in Data Streams.- Frequent Pattern Mining in Data Streams.- A Survey of Change Diagnosis Algorithms in Evolving Data Streams.- Multi-Dimensional Analysis of Data Streams Using Stream Cubes.- Load Shedding in Data Stream Systems.- The Sliding-Window Computation Model and Results.- A Survey of Synopsis Construction in Data Streams.- A Survey of Join Processing in Data Streams.- Indexing and Querying Data Streams.- Dimensionality Reduction and Forecasting on Streams.- A Survey of Distributed Mining of Data Streams.- Algorithms for Distributed Data Stream Mining.- A Survey of Stream Processing Problems and Techniques in Sensor Networks.