Updating Algorithm for Association Rules Based on Fully Mining Incremental Transactions
基于充分挖掘增量事务的关联规则更新算法

Incremental Association rules Mining is an important content of data mining technology.This study proposes a new algorithm,called the Entirety Update Frequent Itemsets Algorithm(EUFIA)for efficiently incrementally mining association rules from large transaction database.Rather than rescanning the original database for some new generated frequent itemsets,EUFIA partitions the incremental database logically according to unit time interval,then accumulates the occurrence counts of new generated frequent itemsets and deletes infrequent itemsets obviously by backward method.Thus,EUFIA can discover newly generated frequent itemsets more efficiently and need rescan the original database only once to get overall frequent itemsets in the final database if necessary.EUFIA has good scalability in our simulation.