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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/20160

    Title: Rough Set Theory in analyzing the attributes of combination values for the insurance market
    Authors: Shyng, Jhieh-yu;Wang, Fang-kuo;Tzeng, Gwo-hshiung;吳坤山;Wu, Kun-shan
    Contributors: 淡江大學企業管理學系
    Keywords: Rough Set Theory;Combination values;Insurance marketing;Decision rule;Expert knowledge
    Date: 2007-01-01
    Issue Date: 2009-11-30 12:35:49 (UTC+8)
    Publisher: Elsevier
    Abstract: Based on Rough Set Theory, this research addresses the effect of attributes/features on the combination values of decisions that insurance companies make to satisfy customers’ needs. Attributes impact on combination values by yielding sets with fewer objects (such as one or two objects), which increases both the lower and upper approximations. It also increases the decision rules, and degrades the precision of decisions. Our approach redefines the value set of attributes through expert knowledge by reducing the independent data set and reclassifying it. This approach is based on an empirical study. The results demonstrate that the redefined combination values of attributes can contribute to the precision of decisions in insurance marketing. Following an empirical analysis, we use a hit test that incorporates 50 validated sample data into the decision rule so that the hit rate reaches 100%. The results of the empirical study indicate that the generated decision rules can cover all new data. Consequently, we believe that the effects of attributes on combination values can be fully applied in research into insurance marketing.
    Relation: Expert Systems with Applications 32(1), pp.56-64
    DOI: 10.1016/j.eswa.2005.11.002
    Appears in Collections:[Graduate Institute & Department of Business Administration] Journal Article

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