| 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
|
| 会议名称 | 4th IEEE International Conference on Data Mining
|
| 页码 | 407-410
|
| 会议日期 | NOV 01-04,
|
| 会议地点 | Brighton, ENGLAND
|
| 收录类别 | istp
; ieee
|
| 出版地 | 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
|
| 出版者 | FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS
|
| ISBN | 0-7695-2142-8
|
| 部门归属 | Chinese Acad Sci, Inst Software, Beijing, Peoples R China.
|
| 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 |
| 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
|
| 主办者 | IEEE Comp Soc, TCCI, IEEE Comp Soc, TCPAMI, IBM Res, StatSoft Ltd, Web Intelligence Consortium
|
| 语种 | 英语
|
| 内容类型 | 会议论文
|
| URI标识 | http://ir.iscas.ac.cn/handle/311060/12954
|
| 专题 | 中国科学院软件研究所
|
推荐引用方式
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.
|
修改评论