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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/65114


    Title: 以基因演算法探討 GSP 參數之研究;Tuning GSP parameters with GA
    Authors: 鄭洧奇;Jheng,Wei-ci
    Contributors: 企業管理學系
    Keywords: 序列模式挖掘;GSP法;基因演算法;Sequential pattern mining;GSP;GA
    Date: 2014-07-16
    Issue Date: 2014-10-15 14:40:54 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 中文摘要
    在資料探勘的領域中,關聯法則可以顯示出當顧客購買產品時,哪些產品會同時被
    購買,學者利用此特性發展出購物籃分析法則,來為企業擬訂銷售上的策略。
    如同大家所知,資料無時無刻都在改變,當新的資料產生時,舊的資料將被取代。
    在資料庫中,時間就成為一個非常重要的屬性,伴隨而生的探勘工具,稱之為序列挖掘
    模式(GSP)。
    GSP 法即是利用時間戳記的屬性,來找到具有序列模式的產品組合。然而,GSP 法
    的參數是透過使用者自行輸入的,運算的結果可能會因為參數設置不當,導致每次運算
    結果不穩定。本研究使用參數庫的設置結合 GSP 法以及基因演算法,透過不斷地演化改
    進,找到適當參數使得結果越趨穩定。
    本實驗以一中型超市驗證結果,發現與隨機輸入參數進行比較後,本研究所提出的
    方法所找到的參數明顯優於隨機設定的參數。

    關鍵字:序列模式挖掘、GSP 法、基因演算法;Tuning GSP parameters with GA

    ABSTRACT
    In data mining, association rules can be shown when customers buy products, which
    products will be purchased at the same time. Scholars use this feature to develop market basket
    analysis to formulate marketing strategies for business.
    As we know, the data are changing all the time. When new data generate, the old data will
    be replaced. In the database, time become a very important attribute. And new data mining
    method have been proposed, called generalized sequential patterns (GSP).
    GSP uses time stamp to find the product portfolio with sequential patterns. However, the
    GSP parameter is user-defined. The result of the operation may be unstable, because of the
    parameter setting incorrectly. Tuning the parameters used in this study combined GSP and
    genetic algorithm (GA) to improve the result continuously, to find the appropriate parameters.
    In the experiment, we use a medium-sized supermarket verify the results and found that
    after comparing with random input parameters, the parameters of the proposed method found
    significantly better than a random set of parameters.


    Keywords:Sequential pattern mining、GSP、GA
    Appears in Collections:[企業管理研究所] 博碩士論文

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