DMCA
Multi-Level Association Rule Mining: An Object-Oriented Approach based on Dynamic Hierarchies (1996)
| Citations: | 6 - 0 self |
BibTeX
@TECHREPORT{Fortin96multi-levelassociation,
author = {Scott Fortin and Ling Liu and Randy Goebel},
title = {Multi-Level Association Rule Mining: An Object-Oriented Approach based on Dynamic Hierarchies},
institution = {},
year = {1996}
}
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Abstract
Previous studies in data mining have yielded efficient algorithms for discovering association rules. But it is well-known problem that the two controlling measures of support and confidence, when used as the sole definition of relevant association rules, are too inclusive --- interesting rules are included with many uninteresting cases. A typical approach to this problem is to augment the thresholds with domainspecific knowledge, in the form of one or more business-goal-driven classification taxonomies. Most existing proposals use the relational approach to organize and maintain the required multi-level concept hierarchies and their domain-dependent components. We present the motivation for a necessary extension to existing uses of such multi-level hierarchies, and describe an implementation that is better suited than the typical relational paradigm for focusing the search and regulating the mining of association rules both at multi-levels within one concept hierarchy, and across multi...
Keyphrases
multi-level association rule mining dynamic hierarchy object-oriented approach association rule relevant association rule relational approach data mining typical relational paradigm previous study efficient algorithm inclusive interesting rule domain-dependent component multi-level hierarchy typical approach concept hierarchy necessary extension domainspecific knowledge sole definition many uninteresting case business-goal-driven classification taxonomy well-known problem required multi-level concept hierarchy
