关键词: 关联规则, 增量更新, 完全频繁项集, 准频繁项集, 弱频繁项集

Abstract: Incremental Association rules Mining is an important content of data mining technology. This study proposes a new algorithm, called the District Classifications Update Frequent Itemsets Algorithm (DCUFIA) for efficiently incrementally mining association rules from large transaction database. Rather than rescanning the original database for some new generated frequent itemsets, DCUFIA 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. Besides, it divides these frequent itemsets into three categories. DCUFIA need not rescan the original database. So it can discover new frequent itemsets more efficiently. DCUFIA has good scalability in our simulation.

Key words: association rules, incremental updating, entirety frequent itemsets, quasi-frequent itemsets, weak frequent itemsets