Title
Mining frequent items in a stream using flexible windows Mining frequent items in a stream using flexible windows
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
Amsterdam ,
Subject
Computer. Automation
Source (journal)
Intelligent data analysis. - Amsterdam
Volume/pages
12(2008) :3 , p. 293-304
ISSN
1088-467X
1088-467X
ISI
000257115300004
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
Abstract
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.
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