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• W2140790334 abstract "Mining generalized association rules with fuzzy taxonomic structures has been recognized as a important extension of generalized associations mining problem. To date most work on this problem, however, required the taxonomies to be static, ignoring the fact that the taxonomies of items cannot necessarily be kept unchanged. For instance, some items may be reclassified from one hierarchy tree to another for more suitable classification, abandoned from the taxonomies if they will no longer be produced, or added into the taxonomies as new items. Additionally, the membership degrees expressing the fuzzy classification may also need to be adjusted. Under these circumstances, effectively updating the discovered generalized association rules is a crucial task. In this paper, we examine this problem and propose two novel algorithms, called FDiffET and FDiff_ET2, to update the discovered frequent generalized itemsets." @default.
• W2140790334 created "2016-06-24" @default.
• W2140790334 creator A5008185438 @default.
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• W2140790334 date "2010-07-01" @default.
• W2140790334 modified "2023-09-25" @default.
• W2140790334 title "Updating generalized association rules with evolving fuzzy taxonomies" @default.
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• W2140790334 doi "https://doi.org/10.1109/fuzzy.2010.5584845" @default.
• W2140790334 hasPublicationYear "2010" @default.
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