Efficient automatic discovery of 'hot' itemsets

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	2014-03-01T01:53:20Z
dc.date.available	2014-03-01T01:53:20Z
dc.date.issued	2004	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/26959
dc.subject	Association Rule	en
dc.subject	Data Mining	en
dc.title	Efficient automatic discovery of 'hot' itemsets	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ipl.2004.01.013	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ipl.2004.01.013	en
heal.publicationDate	2004	en
heal.abstract	In real life applications the dominant model of the single support, which assumed all itemsets to be of the same nature and importance proved defective. The non-homogeneity of the itemsets on one hand and the non-uniformity of their number of appearances on the other require that we use different approaches. Some techniques have been proposed thus far trying to address	en
heal.journalName	Information Processing Letters	en
dc.identifier.doi	10.1016/j.ipl.2004.01.013	en