Post-mining: Maintenance of association rules by weighting

Zhang, S; Zhang, C; Yan, X

Post-mining: Maintenance of association rules by weighting

Zhang, S Zhang, C

Yan, X

Permalink

Publication Type:: Journal Article
Citation:: Information Systems, 2003, 28 (7), pp. 691 - 707
Issue Date:: 2003-10-01

Closed Access

	Filename	Description	Size
	2003000457.pdf		258.27 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Zhang, S	en_US
dc.contributor.author	Zhang, C https://orcid.org/0000-0001-5715-7154	en_US
dc.contributor.author	Yan, X	en_US
dc.date.issued	2003-10-01	en_US
dc.identifier.citation	Information Systems, 2003, 28 (7), pp. 691 - 707	en_US
dc.identifier.issn	0306-4379	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5197
dc.description.abstract	This paper proposes a new strategy for maintaining association rules in dynamic databases. This method uses weighting technique to highlight new data. Our approach is novel in that recently added transactions are given higher weights. In particular, we look at how frequent itemsets can be maintained incrementally. We propose a competitive model to 'promote' infrequent itemsets to frequent itemsets, and to 'degrade' frequent itemsets to infrequent itemsets incrementally. This competitive strategy can avoid retracing the whole data set. We have evaluated the proposed method. The experiments have shown that our approach is efficient and promising. © 2003 Elsevier Science Ltd. All rights reserved.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0343109
dc.relation.ispartof	Information Systems	en_US
dc.relation.isbasedon	10.1016/S0306-4379(02)00079-0	en_US
dc.subject.classification	Information Systems	en_US
dc.title	Post-mining: Maintenance of association rules by weighting	en_US
dc.type	Journal Article
utslib.citation.volume	7	en_US
utslib.citation.volume	28	en_US
utslib.for	080604 Database Management	en_US
utslib.for	0806 Information Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (International)
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - ACRI - Australia China Relations Institute
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.issue	7	en_US
pubs.publication-status	Published	en_US
pubs.volume	28	en_US

Abstract:

This paper proposes a new strategy for maintaining association rules in dynamic databases. This method uses weighting technique to highlight new data. Our approach is novel in that recently added transactions are given higher weights. In particular, we look at how frequent itemsets can be maintained incrementally. We propose a competitive model to 'promote' infrequent itemsets to frequent itemsets, and to 'degrade' frequent itemsets to infrequent itemsets incrementally. This competitive strategy can avoid retracing the whole data set. We have evaluated the proposed method. The experiments have shown that our approach is efficient and promising. © 2003 Elsevier Science Ltd. All rights reserved.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/5197