一个基于网格服务的分布式关联规则挖掘算法  

Distributed Algorithm for Mining Association Rules with the Grid Services

作　　者：赵辉[1] 王黎明[1] 

机构地区：[1]郑州大学信息工程学院,河南郑州450052

出　　处：《小型微型计算机系统》2006年第8期1544-1548,共5页Journal of Chinese Computer Systems

摘　　要：分布式关联规则挖掘在知识发现中占着不可忽视的地位,在以往分布式算法的基础上提出了一个加优先权值的PDDM算法,并将修改后的算法与抽样算法、知识网格的思想相结合形成一个GDS算法.GDS算法改善了以往分布式算法中通信量过载,算法难于扩展的问题,而且只扫描一遍数据库,减缓了大数据集挖掘中的I/O问题.理论分析和试验结果表明提出的算法是有效可行的.Distributed data mining for association rules plays an important role in knowledge discovery. This paper presents a PDDM algorithm with priority on the basic of previous algorithm and a GDS algorithm which combines PDDM algorithm with the Sampling algorithm and Knowledge Grid＇s idea. The GDS algorithm, which improves the scalability and I/O problem effectively, decreases the communication of previous algorithm, and scans the database single time. Theory analysis and experimental results show the feasibility and effectiveness of the algorithm.

关 键 词：数据挖掘 分布式 关联规则 抽样算法 知识网格 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]