An Incremental Updating Algorithm forOnline Mining Association Rules

被引：0

作者：

Jia Yubo ^{[1
]}

Duan Yuntao ^{[1
]}

Wang Yongli ^{[2
]}

机构：

[1] Zhejiang Sci Tech Univ, Inst Informat & Electron, Hangzhou 310018, Zhejiang, Peoples R China

[2] Nanjing Univ Sci & Technol, Dept Commun Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China

来源：

WISM: 2009 INTERNATIONAL CONFERENCE ON WEB INFORMATION SYSTEMS AND MINING, PROCEEDINGS | 2009年

关键词：

data mining; association rules; incremental updating; online mining;

D O I：

10.1109/WISM.2009.37

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Aimed at the limitation of the current FUP algorithm, which readily led to the low efficiency of frequent itemset of the updated database, a novel association rules mining algorithm named QAIS which is different from the classical dual phrase was proposed. On the basis of QAIS, an improved association rules mining algorithm named AIU was put forward further. AIU can efficiently maintain association rules when the transaction database was updated. At the same time, the minimum support and confidence were not changed. Experiments showed the proposed algorithm was appropriate to online association rules mining.

引用

页码：144 / +

页数：2

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