Infrequent Item mining in multiple data streams
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Date
2007Type
Conference Paper
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Saha, B. and Lazarescu, M. and Venkatesh, S. 2007. Infrequent Item mining in multiple data streams, in Seventh IEEE International Conference on Data mining, ICDM workshops, Oct 28-31 2007, pp. 569-574. Omaha, USA: IEEE.
Source Title
Proceedings of the 7th IEEE International conference on Data mining and associated workshops
Source Conference
2nd international workshop on data stream mining and management 2007 in conjunction with the 2007 International conference on Data mining
ISBN
School
Department of Computing
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Abstract
The problem of extracting infrequent patterns from streams and building associations between these patterns is becoming increasingly relevant today as many events of interest such as attacks in network data or unusual stories in news data occur rarely. The complexity of the problem is compounded when a system is required to deal with data from multiple streams. To address these problems, we present a framework that combines the time based association mining with a pyramidal structure that allows a rolling analysis of the stream and maintains a synopsis of the data without requiring increasing memory resources. We apply the algorithms and show the usefulness of the techniques.
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