| 基于多参数随机扰动的布尔规则挖掘 |
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| 引用本文： | 陈芸,张伟,周霆,邹汉斌.基于多参数随机扰动的布尔规则挖掘[J].计算机工程,2006,32(10):63-65. |
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| 作者姓名： | 陈芸 张伟 周霆 邹汉斌 |
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| 作者单位： | 1. 江南大学信息工程学院,无锡,214036;江苏信息职业技术学院计算机系,无锡,21410
2. 江南大学信息工程学院,无锡,214036 |
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| 摘 要： | 在MASK算法基础上提出了基于多参数随机扰动后布尔规则的挖掘过程，通过对实验结果的评估分析，表明该算法能够提供较高的隐私保护，并讨论了隐私保护及挖掘精度之间的关系。最后对未来多参数随机扰动数据挖掘研究进行了展望。
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| 关 键 词： | 随机扰动 重构 频集 |
| 文章编号： | 1000-3428（2006）10-0063-03 |
| 收稿时间： | 05 13 2005 12:00AM |
| 修稿时间： | 2005-05-13 |
Boolean Rule Mining Based on Multi-factor Random Perturbation |
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| CHEN Yun,ZHANG Wei,ZHOU Ting,ZOU Hanbin.Boolean Rule Mining Based on Multi-factor Random Perturbation[J].Computer Engineering,2006,32(10):63-65. |
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| Authors: | CHEN Yun ZHANG Wei ZHOU Ting ZOU Hanbin |
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| Affiliation: | 1. School of Information Engineering, Southern Yangtze University, Wuxi 214036; 2. Department of Computer, Jiangsu Information Technology College, Wuxi 214101 |
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| Abstract: | This paper presents a process of boolean rule mining based on multi-factor random perturbation, and analyzes the consequent outcome that indicates the algorithm can provide stronger privacy protection. It discusses the relation of privacy preserving and data mining accuracy. Then, it covers an initial study on the future directions for multi-factor random perturbation in the area of data mining. |
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| Keywords: | Random perturbation Reconstruction Frequency itemsets |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
