Privacy-Preserving Data Mining Algorithm Quantum Ant Colony Optimization

被引：0
|
作者：
Wu Jue [1 ]
Yang Lei [1 ]
Peng Lingxi
Liu Feng [2 ,3 ]
机构：
[1] Southwest Univ Sci & Technol, Coll Comp Sci & Technol, Mianyang, Sichuan, Peoples R China
[2] Guangzhou Univ, Coll Comp Sci & Educ Software, Guangzhou, Guangdong, Peoples R China
[3] Wuhan Univ, Int Sch Software, Wuhan, Peoples R China
来源：
APPLIED MATHEMATICS & INFORMATION SCIENCES | 2013年 / 7卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Quantum Ant colony optimization; Bayesian network; data mining;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Bayesian network has been used extensively in data mining. The Privacy-Preserving data mining algorithm based on quantum ant colony optimization is proposed in this paper. The algorithm is based on distributed database. The algorithm is divided into two steps. In the first step, the modified quantum ant colony optimization algorithm is used to get the local Bayesian network structure. The purpose of the second step is getting the global Bayesian network structure by using local ones. In order to protect the privacy, the secure sum is used in the algorithm. The algorithm is proved to be convergent on theory. Some experiments have been done on the algorithm, and the results proved that the algorithm is feasible.
引用
收藏
页码：1129 / 1135
页数：7
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