AN INCREMENTAL UPDATING ALGORITHM FOR MINING ASSOCIATION RULES

被引：0

作者：

Xu Baowen Yi Tong Wu Fangjun Chen Zhenqiang(Department of Computer Science & Engineering

机构：

来源：

Journal of Electronics(China) | 2002年 / 04期

基金：

中国国家自然科学基金;

关键词：

Data mining; Association rules; Support function; Frequent pattern tree;

D O I：

暂无

中图分类号：

TP301.6 [算法理论];

学科分类号：

081202 ;

摘要：

In this letter, on the basis of Frequent Pattern(FP) tree, the support function to update FP-tree is introduced, then an Incremental FP (IFP) algorithm for mining association rules is proposed. IFP algorithm considers not only adding new data into the database but also reducing old data from the database. Furthermore, it can predigest five cases to three cases. The algorithm proposed in this letter can avoid generating lots of candidate items, and it is high efficient.

引用

页码：403 / 407

页数：5

共 3 条

[1] Fast algorithms for mining association rules, Proc. R. Agrawal,et al. of the 20th Int’l Conference on Very Large Databases, Santiago, Chile, Sept . 1994
[2] Efficient algorithms for discovering frequent sets in incremental databases, In Proc. R. Feldman,et al. 1997 SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, Tucson,Arizona, May . 1997
[3] Mining frequent patterns without candidate generation, Proc of ACM SIGMOD Conf. J. Han,et al. on Management of Data, Dallas, TX . 2000

← 1 →