[1]陆建江,徐宝文,邹晓峰,等.模糊关联规则的并行挖掘算法[J].东南大学学报(自然科学版),2005,35(2):165-170.[doi:10.3969/j.issn.1001-0505.2005.02.001]
 Lu Jianjiang,Xu Baowen,Zou Xiaofeng,et al.Parallel mining algorithm for fuzzy association rules[J].Journal of Southeast University (Natural Science Edition),2005,35(2):165-170.[doi:10.3969/j.issn.1001-0505.2005.02.001]
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模糊关联规则的并行挖掘算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
35
期数:
2005年第2期
页码:
165-170
栏目:
计算机科学与工程
出版日期:
2005-03-20

文章信息/Info

Title:
Parallel mining algorithm for fuzzy association rules
作者:
陆建江12 徐宝文12 邹晓峰3 康达周1
1 东南大学计算机科学与工程系, 南京 210096; 2 江苏省软件质量研究所, 南京 210096; 3 解放军理工大学通信工程学院, 南京 210007
Author(s):
Lu Jianjiang12 Xu Baowen12 Zou Xiaofeng3 Kang Dazhou1
1 Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China
2 Jiangsu Institute of Software Quality, Nanjing 210096, China
3 Institute of Communication Engineering, PLA University of Science and Technology, Nanjing 210007, China
关键词:
数据挖掘 数量型属性 模糊聚类 关联规则 并行
Keywords:
data mining quantitative attribute fuzzy cluster association rules parallel
分类号:
TP311.13
DOI:
10.3969/j.issn.1001-0505.2005.02.001
摘要:
介绍了模糊关联规则挖掘算法的基本思想及实现步骤,提出了模糊关联规则的并行挖掘算法.并行挖掘算法采用并行的模糊c-均值算法将数量型属性划分成若干个模糊集,并借助模糊集软化属性的划分边界.用改进布尔型关联规则的并行挖掘算法来发现频繁模糊属性集.最后由多个处理器并行地产生满足最小模糊信任度的模糊关联规则.在分布式互连的PC/工作站环境下进行性能分析,结果表明并行的挖掘算法具有好的可扩展性、规模增长性和加速比性能.
Abstract:
A parallel algorithm for mining fuzzy association rules is presented and its principle and steps are discussed. In this algorithm, the quantitative attributes are partitioned into several fuzzy sets by parallel fuzzy c-means algorithm. By means of fuzzy sets the partition boundary of the attributes is softened. Then, the parallel algorithm for mining Boolean association rules is improved to discover frequent fuzzy attributes. Finally, the fuzzy association rules with least fuzzy confidence are generated by all processors. This algorithm has been implemented at distributively linked PC/workstation. The experiment results show that the parallel mining algorithm has fine scaleup, sizeup and speedup.

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金资助项目(60373066,60303024)、国家重点基础研究发展计划(973计划)资助项目(2002CB312000)、国家教育部博士点基金资助项目(20020286004).
作者简介: 陆建江(1968—),男,博士,副教授, jjlu@seu.edu.cn.
更新日期/Last Update: 2005-03-20