摘要
对垂直分布于不同站点的数据进行联合关联规则挖掘是一个重要的研究方向,然而已有的算法挖掘得到的都是全局单维关联规则,不能处理多维数据集并得到全局多维关联规则。针对此问题提出一种数据两方垂直分布条件下的多维关联规则挖掘算法TDDM(Two Part Vertically Distributed Data Mining),该算法结合数据立方体技术,直接在垂直分布于两方的数据上进行挖掘,得到多维关联规则。理论分析和实验结果表明,该算法可以有效挖掘数据两方垂直分布条件下的多维关联规则。
It is an important research direction that for the data vertically distributed in different parts the joint association rules mining is conducted. However what gained from the existing algorithms are all the global association rules in single dimension, and they cannot deal with the multidimensional data and get multidimensional global association rules. To solve this problem, we propose a new algorithm TDDM （two-part vertically distributed data mining）, it is a multidimensional association rules mining algorithm under the condition of data distributed vertically on two parts. Combining the technology of data cube, the algorithm directly mine the data distributed vertically on two parts and obtains the multidimensional association rules. Theoretical analysis and experimental results show that the TDDM can effectively mine the multidimensional association rules under the condition of data vertically distributed on two parts.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第1期18-21,80,共5页
Computer Applications and Software
基金
河北省自然科学基金青年基金项目(G2011203195)
河北省社会科学发展研究课题青年课题(201204040)
关键词
数据挖掘
数据两方垂直分布
数据立方体
多维关联规则
频繁谓词集
Data mining Data vertically distributed on two parts Data cube Multidimensional association rules Frequentpredicate sets
