In this study, a general incremental updating technique is proposed for maintaining the frequent itemsets discovered in a database in the cases including insertion, deletion, and modification of transactions in the database. An efficient algorithm, called AFPIM (Adjusting FP-tree for Incremental Mining), is designed based on adjusting FP-tree structures. Our approach uses a FP-tree structure to store the compact information of transactions involving frequent and pre-frequent items in the original database. In most cases, without needing to rescan the original database, the new FP-tree structure of the updated database can be obtained by adjusting FP-tree of the original database according to the changed transactions. Experimental results show that AFPIM outperforms the existing algorithms in terms of the execution time.
|頁（從 - 到）||417-424|
|期刊||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|出版狀態||已發佈 - 2004 十二月 1|
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