Skip navigation
Skip navigation

Efficient Computation of Frequent Itemsets In A Subcollection of Multiple Set Families

Shen, Hong; Liang, Weifa; Ng, Jack C

Description

Many applications need to deal with the additive and multiplicative subcollections over a group of set families (databases). This paper presents two efficient algorithms for computing the frequent itemsets in these two types of subcollections respectively. Let T be a given subcollection of set families of total size m whose elements are drawn from a domain of size n. We show that ifT is an additive subcollection we can compute all frequent itemsets in T in O(m2n/(pn) + log p) time on an EREW...[Show more]

dc.contributor.authorShen, Hong
dc.contributor.authorLiang, Weifa
dc.contributor.authorNg, Jack C
dc.date.accessioned2015-12-13T23:24:09Z
dc.date.available2015-12-13T23:24:09Z
dc.identifier.issn0350-5596
dc.identifier.urihttp://hdl.handle.net/1885/92090
dc.description.abstractMany applications need to deal with the additive and multiplicative subcollections over a group of set families (databases). This paper presents two efficient algorithms for computing the frequent itemsets in these two types of subcollections respectively. Let T be a given subcollection of set families of total size m whose elements are drawn from a domain of size n. We show that ifT is an additive subcollection we can compute all frequent itemsets in T in O(m2n/(pn) + log p) time on an EREW PRAM with 1 ≤ p ≤ m2n/n processors, at a cost of maintaining the occurrences of all itemsets in each individual set family. If T is a multiplicative subcollection, we can compute all itemsets in T in O(mk/p + min {m′/p 2n, n3n log m′/p}) time on an EREW PRAM with 1 ≤ p ≤ min {m,2n} processors, where m′ = min {m,2n}. These present improvements over direct computation of the frequent itemsets on the subcollection concerned.
dc.publisherSlovene Society Informatika
dc.sourceInformatica
dc.subjectKeywords: Algorithms; Database systems; Parallel processing systems; Program processors; Set theory; Frequent itemsets; Multiple set families; Data mining
dc.titleEfficient Computation of Frequent Itemsets In A Subcollection of Multiple Set Families
dc.typeJournal article
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.citationvolume23
dc.date.issued1999
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationMigratedxPub23066
local.type.statusPublished Version
local.contributor.affiliationShen, Hong, Griffith University
local.contributor.affiliationLiang, Weifa, College of Engineering and Computer Science, ANU
local.contributor.affiliationNg, Jack C, University of Queensland
local.bibliographicCitation.issue4
local.bibliographicCitation.startpage543
local.bibliographicCitation.lastpage548
dc.date.updated2015-12-12T09:19:21Z
local.identifier.scopusID2-s2.0-0033356233
CollectionsANU Research Publications

Download

There are no files associated with this item.


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  17 November 2022/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator