Presentation	1996/7/25 Parallel Mining Association Rules with Classification Hierarchy Takahiko Shintani, Masaru Kitsuregawa,
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Abstract(in English)	One of the most important problems in database mining is the discovery of association rules with in large databases. In most cases, classification hierarchies over the data items are available. Users are interested in generating association rules that span different levels of the classification hierarchy. In this paper, we consider the parallel algorithms for mining association rules with classification hierarchy on a shared-nothing environment. We present three parallel algorithms based on the parallel algorithms for single concept level association rules. We implemented these algorithms on a shared-nothing parallel computer. Performance evaluation show that the best algorithm, HPA-ELD, attains good linearity on speedup and is effective for skew handling.
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Paper #	DE96-33
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Committee	DE
Conference Date	1996/7/25(1days)
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Registration To	Data Engineering (DE)
Language	JPN
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Title (in English)	Parallel Mining Association Rules with Classification Hierarchy
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1st Author's Name	Takahiko Shintani
1st Author's Affiliation	Institute of Industrial Science, University of Tokyo()
2nd Author's Name	Masaru Kitsuregawa
2nd Author's Affiliation	Institute of Industrial Science, University of Tokyo
Date	1996/7/25
Paper #	DE96-33
Volume (vol)	vol.96
Number (no)	176
Page	pp.pp.-
#Pages	6
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