Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/7377
Title: Mining frequent items in a stream using flexible windows
Authors: GOETHALS, Bart 
Calders, T.
Dexters, N.
Issue Date: 2006
Source: ECML/PKDD 2006 International Workshop on Knowledge Discovery from Data Streams (IWKDDS 06).
Abstract: In this paper we study the problem of finding frequent items in a continuous stream of items. 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 momry requirements of the algorithm are extremely small for many different realistic data distributions.
Document URI: http://hdl.handle.net/1942/7377
Category: R2
Type: Research Report
Appears in Collections:Research publications

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