Title: | mining ratio rules via principal sparse non-negative matrix factorization |
Author: | Hu CY
; Zhang BY
; Yan SC
; Yang Q
; Yan J
; Chen Z
; Ma WY
|
Conference Name: | 4th IEEE International Conference on Data Mining
|
Conference Date: | NOV 01-04,
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Issued Date: | 2004
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Conference Place: | Brighton, ENGLAND
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Keyword: | 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
|
Publisher: | FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS
|
Publish Place: | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
|
Indexed Type: | istp
; ieee
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ISBN: | 0-7695-2142-8
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Department: | Chinese Acad Sci, Inst Software, Beijing, Peoples R China.
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Sponsorship: | IEEE Comp Soc, TCCI, IEEE Comp Soc, TCPAMI, IBM Res, StatSoft Ltd, Web Intelligence Consortium
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English Abstract: | 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 |
Language: | 英语
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Content Type: | 会议论文
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URI: | 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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