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›› 2005, Vol. 31 ›› Issue (11): 83-.

• 论文 • 上一篇    下一篇

量化关联规则的隐私保持挖掘方法

陈子阳,马朝虹,李宇佳,刘国华   

  1. 燕山大学计算机科学与工程系,燕山大学计算机科学与工程系,燕山大学计算机科学与工程系,燕山大学计算机科学与工程系 秦皇岛 066004,秦皇岛 066004,秦皇岛 066004,秦皇岛 066004
  • 发布日期:2005-06-15

Privacy-preserving Mining Method of Quantitative Association Rule

CHEN Ziyang, MA Zhaohong, LI Yujia, LIU Guohua   

  1. (Department of Computer Science and Engineering, Yanshan University, Qinhuangdao 066004)
  • Published:2005-06-15

摘要: 根据数据库中量化属性值和分类属性值数量的不同,分别提出了基于布尔关联规则的量化关联规则隐私保持挖掘方法和基于部分变换机制的量化关联规则隐私保持挖掘方法。对于每一种方法都进行了隐私度和正确度分析,并通过实验证明了其正确性和可行性。

关键词: 量化关联规则, 隐私保持, 数据挖掘

Abstract: Considering the size of quantitative attribute values and categorical attribute values in databases, the paper presents two quantitative association rules mining methods considering privacy-preserving respectively, one bases on boolean association rules, the other bases on partially transform measure. To each approach, the privacy and accuracy are analyzed, and the correctness and feasibility are proved by experiments.

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