| 比较两种挖掘正态关联规则方法 |
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| 引用本文： | 陆建江,徐勇,宋自林.比较两种挖掘正态关联规则方法[J].解放军理工大学学报,2000,1(5):51-54. |
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| 作者姓名： | 陆建江 徐勇 宋自林 |
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| 作者单位： | 陆建江（解放军理工大学通信工程学院,江苏南京 210016）;徐勇（解放军理工大学理学院,江苏南京211101）;宋自林（解放军理工大学指挥自动化学院,江苏南京 210016） |
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| 摘 要： | 首先采用两种聚类方法确定正态模糊数的两个参数,并借助正态模糊数模型来软化数量属性论域的划分边界,由此生成一系列的正态关联规则.接着给出正态关联规则的挖掘方法,此方法能挖掘出所有有意义的正态关联规则.最后对两种挖掘正态关联规则的方法进行了比较.
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| 关 键 词： | 数据挖掘 FCM算法 聚类 正态关联规则 |
| 文章编号： | 1009-3443(2000)05-0051-04 |
| 修稿时间： | 1999年12月29 |
Comparing Two Methods of Mining Normal Association Rules |
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| LU Jian jiang,XU Yong and SONG Zi lin.Comparing Two Methods of Mining Normal Association Rules[J].Journal of PLA University of Science and Technology(Natural Science Edition),2000,1(5):51-54. |
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| Authors: | LU Jian jiang XU Yong and SONG Zi lin |
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| Institution: | Institute of Communications Engineering, PLAUST, Nanjing 210016, China;Institute of Sciences, PLAUST, Nanjing 211101, China;Institute of Command Automation, PLAUST |
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| Abstract: | In this paper, two parameters of normal fuzzy numbers are determined by two clustering methods. Then the normal fuzzy number model is adopted to soften the domain partition boundary of the quantitative attributes and a series of linguistic value association rules are generated. The method of mining normal association rules is also provided. With this method, all interesting normal association rules can be mined. Two methods of mining normal association rules are compared in the last part. |
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| Keywords: | date mining fuzzy c means algorithm clustering normal association rules |
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