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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/69130
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/69130

    Title: Efficient Graph-Based Algorithms for Discovering and Maintaining Association Rules in Large Databases
    Authors: 陳良弼
    Lee,Guanling;Lee,K. L.;Chen,Arbee L. P.
    Contributors: 資科系
    Keywords: Association rule;Bit vector;Graph-based approach;Rules maintenance
    Date: 2001
    Issue Date: 2014-08-21 14:53:49 (UTC+8)
    Abstract: In this paper, we study the issues of mining and maintaining association rules in a large database of customer transactions. The problem of mining association rules can be mapped into the problems of finding large itemsets which are sets of items brought together in a sufficient number of transactions. We revise a graph-based algorithm to further speed up the process of itemset generation. In addition, we extend our revised algorithm to maintain discovered association rules when incremental or decremental updates are made to the databases. Experimental results show the efficiency of our algorithms. The revised algorithm is a significant improvement over the original one on mining association rules. The algorithms for maintaining association rules are more efficient than re-running the mining algorithms for the whole updated database and outperform previously proposed algorithms that need multiple passes over the database.
    Relation: Knowledge and Information Systems (SCIE), Springer-Verlag,3,338-355
    Data Type: article
    Appears in Collections:[資訊科學系] 期刊論文

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