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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Bibliographic Details
Published in:	The Journal of computer information systems Vol. 53; no. 3; pp. 14 - 27
Main Author:	Kuthadi, Venu Madhav
Format:	Journal Article
Language:	English
Published:	Stillwater Taylor & Francis 01.03.2013 Taylor & Francis Ltd
Subjects:	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
Online Access:	Get full text
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