A New Data Stream Mining Algorithm for Interestingness-Rich Association Rules

Frequent itemset mining and association rule generation is a challenging task in data stream. Even though, various algorithms have been proposed to solve the issue, it has been found out that only frequency does not decides the significance interestingness of the mined itemset and hence the associat...

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Vydáno v:	The Journal of computer information systems Ročník 53; číslo 3; s. 14 - 27
Hlavní autor:	Kuthadi, Venu Madhav
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Stillwater Taylor & Francis 01.03.2013 Taylor & Francis Ltd
Témata:	Algorithm Algorithms Data mining Data Stream Data Stream Parameters-tuned Interestingness (DSPI) Dimensional analysis Frequency Supporters-tuned Interestingness (FSI) Interestingness Parameters-tuned Interestingness (API) Probability distribution Process controls Streaming media Studies Surveillance
ISSN:	0887-4417, 2380-2057
On-line přístup:	Získat plný text
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