Mining Frequent Intemsets in Memory-Resident Databases

16 Pages Posted: 26 Aug 2006

See all articles by Wim Pijls

Wim Pijls

Erasmus Research Institute of Management (ERIM)

Jan C. Bioch

Erasmus University Rotterdam (EUR) - Centre for Computers and Law; Erasmus Research Institute of Management (ERIM)

Date Written: December 5, 2000

Abstract

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.

Keywords: association rules, datamining, frequent itemsets

JEL Classification: R4, M, M11, C89

Suggested Citation

Pijls, Wim and Bioch, Jan C., Mining Frequent Intemsets in Memory-Resident Databases (December 5, 2000). ERIM Report Series Reference No. ERS-2000-53-LIS, Available at SSRN: https://ssrn.com/abstract=370855

Wim Pijls (Contact Author)

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Jan C. Bioch

Erasmus University Rotterdam (EUR) - Centre for Computers and Law ( email )

3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM)

P.O. Box 1738
3000 DR Rotterdam
Netherlands

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
71
Abstract Views
1,450
rank
387,000
PlumX Metrics