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Article: Effect of adaptive interval configuration on parallel mining association rules

TitleEffect of adaptive interval configuration on parallel mining association rules
Authors
Issue Date2000
PublisherChinese Academy of Sciences, Institute of Software. The Journal's web site is located at http://www.jos.org.cn
Citation
Ruan Jian Xue Bao/Journal Of Software, 2000, v. 11 n. 2, p. 159-172 How to Cite?
AbstractAll current parallel algorithms for mining the association rules follow the conventional level-wise approach. It imposes a synchronization in every iterative computation which degrades greatly their mining performance on a shared-memory multi-processor parallel machine. An asynchronous algorithm APM (asynchronous parallel mixing) has been proposed for mining the association rules on a shared-memory multi-processor machine. All participating processors in APM generate the candidate sets and count their supports independently without synchronization. Furthermore, it can finish the computation with fewer passes of database scanning than required in the level-wise approach. An optimization technique has been developed to enhance APM so that its performance would be insensitive to the data distribution. Two variants of APM and the synchronous algorithm Count Distribution, which is a parallel version of the popular serial mining algorithm Apriori, have been implemented on an SGI Power Challenge SMP parallel machine. The results show that the asynchronous algorithm APM is better than the synchronous algorithm in performance and extensibility.
Persistent Identifierhttp://hdl.handle.net/10722/89152
ISSN
2015 SCImago Journal Rankings: 0.288

 

DC FieldValueLanguage
dc.contributor.authorHu, Kanen_HK
dc.contributor.authorCheung, DWen_HK
dc.contributor.authorXia, Shaoweien_HK
dc.date.accessioned2010-09-06T09:53:02Z-
dc.date.available2010-09-06T09:53:02Z-
dc.date.issued2000en_HK
dc.identifier.citationRuan Jian Xue Bao/Journal Of Software, 2000, v. 11 n. 2, p. 159-172en_HK
dc.identifier.issn1000-9825en_HK
dc.identifier.urihttp://hdl.handle.net/10722/89152-
dc.description.abstractAll current parallel algorithms for mining the association rules follow the conventional level-wise approach. It imposes a synchronization in every iterative computation which degrades greatly their mining performance on a shared-memory multi-processor parallel machine. An asynchronous algorithm APM (asynchronous parallel mixing) has been proposed for mining the association rules on a shared-memory multi-processor machine. All participating processors in APM generate the candidate sets and count their supports independently without synchronization. Furthermore, it can finish the computation with fewer passes of database scanning than required in the level-wise approach. An optimization technique has been developed to enhance APM so that its performance would be insensitive to the data distribution. Two variants of APM and the synchronous algorithm Count Distribution, which is a parallel version of the popular serial mining algorithm Apriori, have been implemented on an SGI Power Challenge SMP parallel machine. The results show that the asynchronous algorithm APM is better than the synchronous algorithm in performance and extensibility.en_HK
dc.languageengen_HK
dc.publisherChinese Academy of Sciences, Institute of Software. The Journal's web site is located at http://www.jos.org.cnen_HK
dc.relation.ispartofRuan Jian Xue Bao/Journal of Softwareen_HK
dc.titleEffect of adaptive interval configuration on parallel mining association rulesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1796-217X&volume=11&issue=1&spage=159&epage=172&date=2000&atitle=Effect+of+Adaptive+Interval+Configuration+on+Parallel+Mining+Association+Rulesen_HK
dc.identifier.emailCheung, DW:dcheung@cs.hku.hken_HK
dc.identifier.authorityCheung, DW=rp00101en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0034138705en_HK
dc.identifier.hkuros51975en_HK
dc.identifier.volume11en_HK
dc.identifier.issue2en_HK
dc.identifier.spage159en_HK
dc.identifier.epage172en_HK
dc.publisher.placeChinaen_HK
dc.identifier.scopusauthoridHu, Kan=7203085144en_HK
dc.identifier.scopusauthoridCheung, DW=34567902600en_HK
dc.identifier.scopusauthoridXia, Shaowei=7202893313en_HK

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