摘要
针对事务数据库的内容不断增加后相应关联规则的更新问题,提出了一种二次挖掘的关联规则增量更新算法(TMIUA)。TMIUA算法充分利用第一次挖掘得到的原数据库中的频繁项集,对新增数据库挖掘得到新增频繁项集;只需对原事务数据库扫描一遍,提高了关联规则的更新效率;并与已有的FUP算法进行了分析比较。
A Two-times-Mining Incremental Updating Algorithm is presented in this paper to solve the problem of association rules because of expansion of a database.Making full use of the frequent item set from original Database,TMIUA get an new added frequent item set by mining the new Database and only scanning the original Database for one time to improve the updating effectiveness,analysis and comparison versus FUP are also made.
出处
《福建商业高等专科学校学报》
2007年第1期99-102,共4页
Journal of Fujian Commercial College
关键词
数据挖掘
关联规则
增量更新
新增频繁项集
Data mining,Association rules,Incremental updating,New added frequent item set
