Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/6669
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dc.contributor.authorBonchi, F.-
dc.contributor.authorGOETHALS, Bart-
dc.date.accessioned2007-12-20T16:09:38Z-
dc.date.available2007-12-20T16:09:38Z-
dc.date.issued2004-
dc.identifier.citationAdvances in Knowledge Discovery and Data Mining. p. 155-160-
dc.identifier.isbn978-3-540-22064-0-
dc.identifier.urihttp://hdl.handle.net/1942/6669-
dc.description.abstractIn the context of mining frequent itemsets, numerous strategies have been proposed to push several types of constraints within the most well known algorithms. In this paper, we integrate the recently proposed ExAnte data reduction technique within the FP-growth algorithm. Together, they result in a very efficient frequent itemset mining algorithm that effectively exploits monotone constraints.-
dc.language.isoen-
dc.publisherBerlin Springer-
dc.relation.ispartofseriesLecture Notes in Computer Science-
dc.titleFP-bonsai: the art of growing and pruning small FP-trees-
dc.title.alternative8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004. Proceedings-
dc.typeJournal Contribution-
local.bibliographicCitation.conferencenameADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS-
dc.identifier.epage160-
dc.identifier.spage155-
local.bibliographicCitation.jcatA1-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.relation.ispartofseriesnr3056-
dc.bibliographicCitation.oldjcatA1-
local.classdsPublValOverrule/no_publishing_delay-
dc.identifier.doi10.1007/b97861-
dc.identifier.isi000221955100017-
item.contributorBonchi, F.-
item.contributorGOETHALS, Bart-
item.fulltextNo Fulltext-
item.accessRightsClosed Access-
item.fullcitationBonchi, F. & GOETHALS, Bart (2004) FP-bonsai: the art of growing and pruning small FP-trees. In: Advances in Knowledge Discovery and Data Mining. p. 155-160.-
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