一种基于聚类分析的事务间关联规则挖掘算法

广西师范大学学报（自然科学版） ›› 2011, Vol. 29 ›› Issue (1): 98-101.

一种基于聚类分析的事务间关联规则挖掘算法

祁艳艳, 任永功

辽宁师范大学计算机与信息技术学院,辽宁大连116081

收稿日期:2010-12-29 发布日期:2018-11-16
通讯作者: 任永功(1972—),男,辽宁兴城人,辽宁师范大学教授,博士。E-mail: renyg@dl.cn
基金资助:
国家自然科学基金资助项目(60603047);教育部留学回国人员科研启动基金资助项目;辽宁省科技计划项目(2008216014);辽宁省教育厅高等学校科研基金资助项目(L2010229);大连市优秀青年科技人才基金资助项目(2008J23J-H026)

An Inter-transaction Association Rules Mining Algorithm Based onClustering Analysis

QI Yan-yan, REN Yong-gong

School of Computer and Information Technology,Liaoning NormalUniversity,Dalian Liaoning 116081,China

Received:2010-12-29 Published:2018-11-16

摘要/Abstract

摘要： 现有算法实现了事务内到事务间最大频繁项目集的转换,能够直接发现不同用户之间的关联关系。但在处理较大的事务数据库时,由于是在原数据库基础上进行关联分析,产生了大量的虚假规则。针对上述问题提出一种基于聚类分析的事务间关联规则挖掘算法,利用聚类分析将初始的复杂的数据集进行约简,去掉冗余数据,缩小数据集,避免了多次扫描数据库和大量的虚假规则的产生。实验结果表明该方法比单独使用事务间的关联规则方法具有更高的效率,能更准确地预测用户的兴趣性。

关键词: Web数据挖掘, 事务间关联规则, 聚类分析, 滑动窗口

Abstract: The association rules between transactions are concentrated on meaningful association between different services in data mining.The existing algorithms can realize the largest conversion of frequent itemsets amongand within affairs,and find the relationship between different users.However,indealing with the affairs of the larger database,a large number of false rules are generated due to the correlation analysis is performed on the original database.This paper proposes a mining algorithm of association rules for inter-transaction among affairs based on cluster analysis.Through simplifying the complex dataset by cluster analysis,the proposed approach can eliminate redundant data,reduse the size of dataset and avoid the need for multipole scanning of the database and the generation of a large number of false rules.Experimental results indicate that the proposed method has higher efficiency and the ability of more precisely predicting the interests of users

Key words: Web data mining, inter-transaction association rules, clustering analysis, sliding window

中图分类号:

TP181

祁艳艳, 任永功. 一种基于聚类分析的事务间关联规则挖掘算法[J]. 广西师范大学学报（自然科学版）, 2011, 29(1): 98-101.

QI Yan-yan, REN Yong-gong. An Inter-transaction Association Rules Mining Algorithm Based onClustering Analysis[J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(1): 98-101.

参考文献

[1] TUNG A K H,LU Hong-jun,HAN Jia-wei,et al.Efficient mining of intertransaetion association rules[J].IEEE Transactions on Knowledge and Data Engineering,2003,15(1):43-56.
[2] CAMPELLO R J G B,HRUSCHKA E R.On comparing two sequence of numbers and its applications to clustering analysis[J].Information Sciences,2009,179(8):1025-1039.
[3] SHI Na,LIU Xu-min,GUAN Yong.Research on k-means clustering algorithm:an improved k-means clustering algorithm[C]//Proceedings of the2010 Third International Symposium on Intelligent Information Technology and Security Informatics.Washington DC:IEEE Comtuter Society,2010:63-67.
[4] LEE A J T,WANG chun-sheng,WENG Wan-Yu,et al.An efficient algorithm for mining closed inter-transaction itemsets[J].Data and Knowledge Engineering,2008,66(1):68-91.
[5] BUZIKASHVILI N.Sliding window technique for the Web log analysis[C]//Proceedings of the 16th international conference on World Wide Web.New York:ACM Press,2007:1213-1214.
[6] 任永功,张琰瑜.一种基于最大频繁项目集的挖掘事务间关联规则方法[J].计算机科学,2008,35(11):185-188.
[7] 艾晶,宋自林,赵靓,等.聚类思想在挖掘关联规则中的运用[J].广西师范大学学报:自然科学版,2009,27(1):117-120.

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