Mining frequent intemsets in memory-resident databases

Due to the present-day memory sizes, a memory-resident database has become a practical option. Consequently, new methods designed to mining in such databases are desirable. In the case of disk-resident databases, breadth-first search methods are commonly used. We propose a new algorithm, based upon depth-first search in a set-enumeration tree. For memory-resident databases, this method turns out to be superior to breadth-first search.

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Year of publication:	2000-12-05
Authors:	Pijls, W.H.L.M. ; Bioch, J.C.
Institutions:	Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
Subject:	frequent itemsets \| association rules \| datamining

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Extent:	application/pdf
Series:	Research Paper. - ISSN 1566-5283.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series RePEc:dgr:eureri Number ERS-2000-53-LIS
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005795608