首页 | 本学科首页   官方微博 | 高级检索  
     

A New Parallel Algorithm for Mining Association Rules
引用本文:丁艳辉 王洪国 高明 谷建军. A New Parallel Algorithm for Mining Association Rules[J]. 东华大学学报(英文版), 2006, 23(6): 76-79
作者姓名:丁艳辉 王洪国 高明 谷建军
作者单位:School of Information Science & Engineering, Shandong Normal University, Jinan 250014
摘    要:Mining association rules from large database is very costly.We develop a parallel algorithm for this task on sharedmemory multiprocessor (SMP). Most proposed parallel algorithms for association rules mining have to scan the database at least two times. In this article, a parallel algorithm Scan Once (SO) has been proposed for SMP,which only scans the database once. And this algorithm is fundamentally different from the known parallel algorithm Count Distribution (CD). It adopts bit matrix to store the database information and gets the support of the frequent itemsets by adopting Vector-And-Operation, which greatly improve the efficiency of generating all frequent itemsets.Empirical evaluation shows that the algorithm outperforms the known one CD algorithm.

关 键 词:关联模式挖掘算法 并行算法 数据处理 信息技术
收稿时间:2006-08-20

A New Parallel Algorithm for Mining Association Rules
DING Yan-hui,WANG Hong-guo,GAO Ming,GU Jian-jun. A New Parallel Algorithm for Mining Association Rules[J]. Journal of Donghua University, 2006, 23(6): 76-79
Authors:DING Yan-hui  WANG Hong-guo  GAO Ming  GU Jian-jun
Abstract:Mining association rules from large database is very costly. We develop a parallel algorithm for this task on shared-memory multiprocessor (SMP). Most proposed parallel algorithms for association rules mining have to scan the database at least two times. In this article, a parallel algorithm Scan Once (SO) has been proposed for SMP, which only scans the database once. And this algorithm is fundamentally different from the known parallel algorithm Count Distribution (CD). It adopts bit matrix to store the database information and gets the support of the frequent itemsets by adopting Vector-And-Operation, which greatly improve the efficiency of generating all frequent itemsets. Empirical evaluation shows that the algorithm outperforms the known one CD algorithm.
Keywords:parallel mining  SMP  association rules
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号