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关联规则是数据挖掘的重要研究内容．由于数据库中频繁追加新数据，使得已挖掘的关联规则发生变化，递增修正技术用于维护与修正关联规则．讨论了关联规则的递增修正问题，提出了递增修正算法（ＦＩＵ）．ＦＩＵ算法通过减小支持率，将频繁模式集合扩大，访问新追加的数据，对关联规则进行修正．ＦＩＵ算法减少了数据的访问，提高了递增修正的速度．分析了支持率和频繁模式集合大小的关系，并对算法ＦＩＵ和算法ＦＵＰ进行了比较．
Association rules is an important research content of data mining. Due to the frequent addition of new data in the database, the mining association rules have been changed, and incremental correction techniques are used to maintain and amend association rules. Discusses the problem of incremental revision of association rules, and proposes an incremental correction algorithm (FIU). The FIU algorithm extends the frequent patterns collection by reducing the support rate, accesses newly added data, and corrects the association rules. The FIU algorithm reduces data access and increases the speed of incremental corrections. The relationship between support rate and frequent pattern set size is analyzed, and the algorithm FIU and algorithm FUP are compared.