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IDA
2008
Springer

Mining frequent items in a stream using flexible windows

12 years 1 months ago
Mining frequent items in a stream using flexible windows
We study the problem of finding frequent items in a continuous stream of itemsets. A new frequency measure is introduced, based on a flexible window length. For a given item, its current frequency in the stream is defined as the maximal frequency over all windows from any point in the past until the current state. We study the properties of the new measure, and propose an incremental algorithm that allows to produce the current frequency of an item immediately at any time. It is shown experimentally that the memory requirements of the algorithm are extremely small for many different realistic data distributions.
Toon Calders, Nele Dexters, Bart Goethals
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where IDA
Authors Toon Calders, Nele Dexters, Bart Goethals
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