Association Rules Algorithm Research in Optical Warning System

被引：0
|
作者：
Hu Chaoju [1 ]
Peng Min [1 ]
机构：
[1] N China Elect Power Univ Comp Sci & Technol, Informat Proc Lib, Baoding 071003, Peoples R China
来源：
2009 INTERNATIONAL FORUM ON INFORMATION TECHNOLOGY AND APPLICATIONS, VOL 3, PROCEEDINGS | 2009年
关键词：
database partition; MIS-tree; frequent pattern; CFP-growth;
D O I：
10.1109/IFITA.2009.242
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Mining association rules with multiple minimum supports is an important research aspect of data mining. In this paper we propose a database partition method to mine the frequent item sets, and use MIS-tree to store the crucial information about frequent patterns. We use the CFP-growth algorithm to mine local frequent patterns and insert them into the global frequent pattern. The experiment on OASN shows that the method is effective to predict the optical warning level
引用
收藏
页码：189 / 192
页数：4
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