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Data Streams Models and Algorithms

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 i...

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Bibliographic Details
Other Authors: Aggarwal, Charu C. (Editor)
Format: eBook
Language:English
Published: New York, NY Springer US 2007, 2007
Edition:1st ed. 2007
Series:Advances in Database Systems
Subjects:
Computer Communication Networks
Multimedia Systems
Information Storage And Retrieval
Artificial Intelligence
Database Management
Data Mining
Computer Networks 
Information Storage And Retrieval Systems
Data Mining And Knowledge Discovery
Multimedia Information Systems
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 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

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