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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/76784
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/76784

    Title: Discovering phenomena - Correlations among association rules
    Authors: Wu, Y.-H.;Chang, M.Y.-C.;Chen, Arbee L. P.
    Contributors: 資科系
    Keywords: Association rules;Hierarchical tree;Data acquisition;Data warehouses;Database systems;Hierarchical systems;Query languages;Trees (mathematics);Data mining
    Date: 2006-01
    Issue Date: 2015-07-21 15:53:25 (UTC+8)
    Abstract: With the growth of various data types, mining useful association rules from large databases has been an important research topic nowadays. Previous works focus on the attributes of data items to derive a variety of association rules. In this paper, we use the attributes of transactions to organize the data as a multiple-attribute hierarchical tree where the multiple-attribute association rules can be efficiently derived. Furthermore, we store the derived rules as a frequent hierarchical tree and allow users to specify various types of queries for finding interesting correlations named phenomena among the rules. We then make experiments to evaluate the performance of our approach.
    Relation: Journal of Internet Technology, 7(1), 1-10
    Data Type: article
    Appears in Collections:[資訊科學系] 期刊論文

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