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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/69145
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/69145

    Title: The analysis of relationships in databases for rule derivation
    Authors: 陳良弼
    Chen,Arbee L. P.
    Contributors: 資科系
    Date: 1996-11
    Issue Date: 2014-08-21 15:01:45 (UTC+8)
    Abstract: Owing to the rapid growth in the sizes of databases, potentially useful information may be embeded in a large amount of data. Knowledge discovery is the search for semantic relationships which exist in large databases. One of the main problems for knowledge discovery is that the number of possible relationships can be very large, thus searching for interesting relationships and reducing the search complexity are important. The relationships can be represented as rules which can be used in efficient query processing. We present a technique to analyze relationships among attribute values and to derive compact rule set. We also propose a mechanism and some heuristics to reduce the search complexity for the rule derivation process. An evaluation model is presented to evaluate the quality of the derived rules. Moreover, in real world, databases may contain uncertain data. We also propose a technique to analyze the relationships among uncertain data and derive probabilistic rules.
    Relation: Journal of Intelligent Information Systems,7(3),235-259
    Data Type: article
    Appears in Collections:[資訊科學系] 期刊論文

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