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Advances in Database Systems #33: Data Streams: Models and Algorithms

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Advances in Database Systems #33: Data Streams: Models and Algorithms Cover

 

Synopses & Reviews

Publisher Comments:

In recent years, the progress in hardware technology has made it possible for organizations to store and record large streams of transactional data.  Such data sets which continuously and rapidly grow over time are referred to as data streams. Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams rather than the database management aspect of streams. This volume covers mining aspects of data streams in a comprehensive style. Each contributed chapter, from a variety of well known researchers in the data mining field, contains a survey on the topic, the key ideas in the field from 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 graduate-level students in computer science. 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.

Synopsis:

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.

Synopsis:

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

Table of Contents

Preface.- 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.- Index.

Product Details

ISBN:
9780387287591
Author:
Aggarwal, Charu C.
Publisher:
Springer
Subject:
Database Management - General
Subject:
Programming - Algorithms
Subject:
Mathematics
Subject:
Computer Science
Subject:
Data mining
Subject:
Computer science -- Mathematics.
Subject:
Data
Subject:
data streams
Subject:
Database
Subject:
frequent pattern mining in streams
Subject:
Models
Subject:
Sensor networks
Subject:
stream classification
Subject:
stream clustering
Subject:
stream mining
Subject:
stream summarization
Subject:
Data Mining and Knowledge Discovery
Subject:
Database management
Subject:
Information storage and retrieval.
Subject:
multimedia information systems
Subject:
Computer Communication Networks
Subject:
Information Systems Applications (incl.Internet)
Subject:
Database design
Copyright:
Edition Description:
Book
Series:
Advances in Database Systems
Series Volume:
33
Publication Date:
20061127
Binding:
HARDCOVER
Language:
English
Illustrations:
Y
Pages:
376
Dimensions:
235 x 155 mm 1560 gr

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Database » Design
Computers and Internet » Software Engineering » Algorithms
Computers and Internet » Software Engineering » Software Management
Reference » Science Reference » Technology

Advances in Database Systems #33: Data Streams: Models and Algorithms New Hardcover
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$209.75 In Stock
Product details 376 pages Springer - English 9780387287591 Reviews:
"Synopsis" by , 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.
"Synopsis" by , This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. 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.
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