An incremental algorithm for mining frequent closed patterns

被引：0

作者：

Shi, Huai-Dong ^{[1
]}

Cai, Ming ^{[1
]}

Wu, Hong-Sen ^{[2
]}

Dong, Jin-Xiang ^{[1
]}

Fu, Hao ^{[1
]}

机构：

[1] College of Computer Science and Technology, Zhejiang University

[2] Zhejiang Police College

来源：

Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2009年 / 43卷 / 08期

关键词：

Closed itemset mining; Data mining; Frequent closed pattern; Knowledge discovery;

D O I：

10.3785/j.issn.1008-973X.2009.08.007

中图分类号：

学科分类号：

摘要：

While mining frequent closed patterns (FCP), the input sequence database dynamically increases in many situations. By analyzing Bide algorithm, the theorem of backward-extension event (BEE) detection was proposed and proved. It shows that the BEE set of any prefix item is non-increasing with the extension of the prefix. Based on the theorem, the accumulation performance of the BEE set was optimized by 4.8% averagely. The FCP tree was defined to represent the final result of FCP mining and its three characteristics were demonstrated. When the frequent item and the prefix are not coexistent in the new input sequence, the results of contiguous FCP mining are equal. And the corresponding theorem was proved. The BideInc algorithm was proposed to incrementally mine FCPs. The experiments validated the algorithm, and the performance was improved by 47% averagely.

引用

页码：1389 / 1395

页数：6

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