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. © Springer-Verlag 2004.
CITATION STYLE
Koh, J. L., & Shieh, S. F. (2004). An efficient approach for maintaining association rules based on adjusting FP-tree structures. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2973, 417–424. https://doi.org/10.1007/978-3-540-24571-1_38
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