An efficient approach for maintaining association rules based on adjusting FP-tree structures

Jia Ling Koh, Shui Feng Shieh

    Research output: Contribution to journalArticlepeer-review

    81 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)417-424
    Number of pages8
    JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume2973
    Publication statusPublished - 2004 Dec 1

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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