Finding Association Rules through Efficient Knowledge Management Technique

被引:1
作者
Anwar, M. A. [1 ]
机构
[1] Al Ghurair Univ, Coll Engn & Comp, Dubai Acad City, U Arab Emirates
关键词
Data Mining; Co-occurrences; Incremental association rules; Dynamic Databases;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
One of the recent research topics in databases is Data Mining, to find, extract and mine the useful information from databases. In case of updating transactions in the database the already discovered knowledge may become invalid. So we need efficient knowledge management techniques for finding the updated knowledge from the database. There have been lot of research in data mining, but Knowledge Management in databases is not studied much. One of the data mining techniques is to find association rules from databases. But most of association rule algorithms find association rules from transactional databases. Our research is a further step of the Tree Based Association Rule Mining (TBAR) algorithm, used in relational databases for finding the association rules. In our approach of updating the already discovered knowledge; the proposed algorithm Association Rule Update (ARU), updates the already discovered association rules found through the TBAR algorithm. Our algorithm will be able to find incremental association rules from relational databases and efficiently manage the previously found knowledge.
引用
收藏
页码:131 / 134
页数:4
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