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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/35231
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/35231


    Title: 選擇商業應用資料探勘方法之框架
    A Framework for Selecting Data Mining Method in Business Application
    Authors: 陳庭鈞
    Chen,Tin Jiun
    Contributors: 諶家蘭
    季延平

    Seng,Jia Lang
    Chi,Yen Ping

    陳庭鈞
    Chen,Tin Jiun
    Keywords: 資料探勘
    商業應用
    選擇方法
    資料探勘演算法
    Data mining
    Business application
    Selection method
    Data mining algorithm
    Date: 2005
    Issue Date: 2009-09-18 14:30:17 (UTC+8)
    Abstract: 由於資訊科技的進步與網路的普及,企業得以收集與儲存大量的資料。使用資訊工具來協助資料處理、資訊擷取、以及產生知識已然變成企業的重要課題之一,所以如何良好運用資料探勘工具成為使用者關注的焦點。由於並非每一個使用者對於資料探勘的原理都有充分的了解,所以如何從探勘工具提供的功能中選用最佳的解決方案並不容易。如果對於探勘結果不滿意而需要調整軟體邏輯,與IT人員的協商溝通卻又曠日費時。

    為了解決這個問題,本研究提出一個演算法選擇方法,藉由分析商業應用的內容,來自動對應到特定的資料探勘方法與演算法,讓選擇演算法的過程更為快速、更系統化,提升利用資料探勘工具解決商業問題的效率。
    Due to the information technology improvement and the growth of internet, companies are able to collect and to store huge amount of data. Using data mining technology to aid the data processing, information retrieval and knowledge generation process has become one of the critical missions to enterprise, so how to use data mining tools properly is users’ concern. Since not every user completely understand the theory of data mining, choosing the best solution from the functions which data mining tools provides is not easy. If user is not satisfied with the outcome of mining, communication with IT employees to adjust the software costs lots of time.

    To solve this problem, a selection model of data mining algorithms is proposed. By analyzing the content of business application, user’s requirement will map to certain data mining category and algorithm. This method makes algorithm selection faster and reasonable to improve the efficiency of applying data mining tools to solve business problems.
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    Description: 碩士
    國立政治大學
    資訊管理研究所
    93356031
    94
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0093356031
    Data Type: thesis
    Appears in Collections:[資訊管理學系] 學位論文

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