Privacy Parallel Algorithm for Mining Association Rules and Its Application in HRM

被引:1
|
作者
Zhang, XuePing [1 ,2 ]
Zhu, YanXia [1 ]
Hua, Nan [3 ]
机构
[1] Henan Univ Technol, Coll Informat Sci & Engn, Zhengzhou 450001, Peoples R China
[2] Minist Educ, Key Lab Spatial Data Mining & Informat Sharing, Fuzhou 350002, Peoples R China
[3] Zhengzhou SuperHW Network Technol Co Ltd, Technol Dept, Zhengzhou 450000, Peoples R China
来源
SECOND INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 2, PROCEEDINGS | 2009年
基金
美国国家科学基金会;
关键词
parallel data mining; rules mining; FP-tree; privacy preserving; Hash assignment strategy;
D O I
10.1109/ISCID.2009.220
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Parallel association rules mining has been improved the efficiency of data mining, and meanwhile concerned with the privacy preserving problem. A simple and effective method of parallel association rules mining which based on privacy protection----Parallel Association Rules Mining Algorithm with Privacy preserving(PARMA-P) has been introduced in this paper; It could achieve effective concealment of frequent item-set and then the association rules by the means of using imported Hash assignment strategy in frequent item sets of FP sub tree could be protected. It has been used in HRM of an enterprise and experiments show that the algorithm can be simple and effective in protection of data privacy.
引用
收藏
页码:296 / +
页数:2
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