An Improved Algorithm for Mining Association Rules Using Multiple Support Values

Kouris, I; Makris, C; Tsakalidis, A

dc.contributor.author	Kouris, I	en
dc.contributor.author	Makris, C	en
dc.contributor.author	Tsakalidis, A	en
dc.date.accessioned	2014-03-01T02:49:18Z
dc.date.available	2014-03-01T02:49:18Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34490
dc.relation.uri	http://www.informatik.uni-trier.de/~ley/db/conf/flairs/flairs2003.html#KourisMT03	en
dc.relation.uri	https://www.aaai.org/Papers/FLAIRS/2003/Flairs03-060.pdf	en
dc.relation.uri	http://www.aaai.org/Papers/FLAIRS/2003/Flairs03-060.pdf	en
dc.subject	Association Rule	en
dc.subject	Association Rule Mining	en
dc.title	An Improved Algorithm for Mining Association Rules Using Multiple Support Values	en
heal.type	conferenceItem	en
heal.publicationDate	2003	en
heal.abstract	Almost all the approaches in association rule mining suggested the use of a single minimum support, technique that either rules out all infrequent itemsets or suffers from the bottleneck of generating and examining too many candidate large itemsets. In this paper we consider the combination of two well-known algorithms, namely algorithm DIC and MSApriori in order to end up with	en
heal.journalName	The Florida AI Research Society Conference	en