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dc.contributor.authorRudra, Amit
dc.contributor.authorGopalan, Raj
dc.contributor.authorSucahyo, Yudho
dc.contributor.editorGedeon, Tamas D.
dc.contributor.editorFung, Lance C.C.
dc.date.accessioned2017-01-30T11:59:44Z
dc.date.available2017-01-30T11:59:44Z
dc.date.created2008-11-12T23:32:57Z
dc.date.issued2003
dc.identifier.citationRudra, Amit and Gopalan, Raj P. and Sucahyo, Yudho. 2003. Efficiently mining frequent patterns from dense datasets using a cluster of computers, in Gedeon, T.D. and Fung, L.C. (ed), AI 2003: advances in artificial intelligence, pp. 233-244. Heidelberg: Springer.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/17116
dc.identifier.doi10.1007/b94701
dc.description.abstract

Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we present an algorithm for finding complete frequent patterns from very large dense datasets in a cluster environment. The data needs to be distributed to the nodes of the cluster only once and the mining can be performed in parallel many times with different parameter settings for minimum support. The algorithm is based on a master-slave scheme where a coordinator controls the data parallel programs running on a number of nodes of the cluster. The parallel program was executed on a cluster of Alpha SMPs. The performance of the algorithm was studied on small and large dense datasets. We report the results of the experiments that show both speed up and scale up of our algorithm along with our conclusions and pointers for further work.

dc.publisherSpringer
dc.titleEfficiently mining frequent patterns from dense datasets using a cluster of computers
dc.typeBook Chapter
dcterms.source.startPage233
dcterms.source.endPage244
dcterms.source.titleAI 2003: advances in artificial intelligence
dcterms.source.seriesLecture Notes in Computer Science
dcterms.source.conferenceCIT 2003: Sixth International Conference on Information Technology
dcterms.source.conferencelocationBhubaneswar, India
dcterms.source.placeHeidelberg
curtin.note

The original publication is available at http://www.springerlink.com

curtin.note

The link to this chapter is: http://springerlink.metapress.com/content/epe5cygrxmncd1mb/fulltext.pdf

curtin.identifierEPR-2587, PUB-CBS-SIS-SA-17794
curtin.accessStatusOpen access
curtin.facultyCurtin Business School
curtin.facultySchool of Information Systems


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