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题名: | mining ratio rules via principal sparse non-negative matrix factorization |
作者: | Hu CY
; Zhang BY
; Yan SC
; Yang Q
; Yan J
; Chen Z
; Ma WY
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会议名称: | 4th IEEE International Conference on Data Mining
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会议日期: | NOV 01-04,
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出版日期: | 2004
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会议地点: | Brighton, ENGLAND
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关键词: | association rules
; principal sparse nonnegative matrix factorization
; principle component analysis
; quantifiable data mining
; quantitative association knowledge
; ratio rules mining
; support measurement
; data mining
; matrix decomposition
; principal compone
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出版者: | FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS
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出版地: | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
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收录类别: | istp
; ieee
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ISBN: | 0-7695-2142-8
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部门归属: | Chinese Acad Sci, Inst Software, Beijing, Peoples R China.
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主办者: | IEEE Comp Soc, TCCI, IEEE Comp Soc, TCPAMI, IBM Res, StatSoft Ltd, Web Intelligence Consortium
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英文摘要: | Association rules are traditionally designed to capture statistical relationship among itemsets in a given database. To additionally capture the quantitative association knowledge, F. Korn et al recently proposed a paradigm named Ratio Rules 4 |
语种: | 英语
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内容类型: | 会议论文
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URI标识: | http://ir.iscas.ac.cn/handle/311060/12954
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Appears in Collections: | 软件所图书馆_会议论文
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01410322.pdf(152KB) | -- | -- | 限制开放 | -- | 联系获取全文 |
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Recommended Citation: |
Hu CY,Zhang BY,Yan SC,et al. mining ratio rules via principal sparse non-negative matrix factorization[C]. 见:4th IEEE International Conference on Data Mining. Brighton, ENGLAND. NOV 01-04,.
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