Association rule mining algorithm of multidimensional sets

被引:2
|
作者
Zhong, Yong [1 ]
Qin, Xiaolin [1 ]
Bao, Lei [1 ]
机构
[1] Institute of Information Science and Technology, Nanjing University of Aeronautics and Astronautics
来源
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | 2006年 / 43卷 / 12期
关键词
Association rule; Data mining; Multidimensional association rule; Multidimensional set;
D O I
10.1360/crad20061213
中图分类号
学科分类号
摘要
Most of multidimensional association rule mining algorithms such as mining algorithms based on data cube assume that an object attribute only has a single-value. In this paper, the attribute value of an object is extended to a multi-value and the concept of multidimensional set is presented, which brings about the semantics of multidimensional set association rule. Based on the semantics, an algorithm to mine association rules of multidimensional sets is given. The algorithm makes use of the restricted characteristics of multidimensional set association rule and can execute a triplicate pruning of candidate sets with a reduction of data set, which makes it a better performance than that of apriori and other algorithms. The performance, correctness and completeness of the algorithm are analyzed, and its effectiveness is also proved by experiments.
引用
收藏
页码:2117 / 2123
页数:6
相关论文
共 8 条
  • [1] Agrawal R., Imielinski T., Swarmi A., Mining association rules between sets of items in large databases, The 1993 ACM Int'l Conf on Management of Data, (1993)
  • [2] Kamber M., Han J., Chiang J.Y., Metarule-guided mining of multi-dimensional association rules using data cubes, The 3rd Int'l Conf on Knowledge Discovery and Data Mining (KDD'97), (1997)
  • [3] Gunzel H., Albrecht J., Lehner W., Data mining in a multidimensional environment, The 3rd East European Conf on Advances in Databases and Information Systems, (1999)
  • [4] Lu H., Feng L., Li Q., Beyond intratransaction association analysis: Mining multidimensional intertransaction association rules, ACM Trans on Information Systems, 18, 4, pp. 423-454, (2000)
  • [5] Li Z., Huang F., Zhou D., Using data cube for mining of hybrid-dimensional association rules, The 2003 Grid and Cooperative Computing, (2003)
  • [6] Xin Y., Ju S., Mining conditional hybrid-dimension association rules on the basis of multi-dimensional transaction database, The 2nd Int'l Conf on Machine Learning and Cybernetics, (2003)
  • [7] Han J., Pei J., Yin Y., Mining frequent patterns without candidate generation, The 2000 ACM SIGMOD Int'l Management of Data, (2000)
  • [8] IBM quest market-basket synthetic data Generator, (2005)