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| mining ratio rules via principal sparse non-negative matrix factorization | |
| Hu CY; Zhang BY; Yan SC; Yang Q; Yan J; Chen Z; Ma WY | |
| 2004 | |
| Conference Name | 4th IEEE International Conference on Data Mining |
| Pages | 407-410 |
| Conference Date | NOV 01-04, |
| Conference Place | Brighton, ENGLAND |
| Indexed Type | istp ; ieee |
| Publish Place | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA |
| Publisher | FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS |
| ISBN | 0-7695-2142-8 |
| Department | Chinese Acad Sci, Inst Software, Beijing, Peoples R China. |
| 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 |
| 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 |
| Sponsorship | IEEE Comp Soc, TCCI, IEEE Comp Soc, TCPAMI, IBM Res, StatSoft Ltd, Web Intelligence Consortium |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/12954 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Hu CY,Zhang BY,Yan SC,et al. mining ratio rules via principal sparse non-negative matrix factorization[C]. 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS,2004:407-410. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 01410322.pdf（152KB） | 开放获取 | -- | Application Full Text | |||
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