商業環境不斷的變遷，各產業間競爭更加的激烈，面對微利時代的來臨，如何提高企業的利潤，保持競爭優勢，成為各個企業所必須面臨的問題。從早期大量生產的產品導向到目前小量多樣的顧客導向，再次說明整個商業型態主流製造業轉向服務業，而不再是單純的買賣關係，以客為尊、顧客至上，做好顧客關係管理 ，將是許多企業奉為圭臬；如何行銷才能提高顧客忠誠度，並從顧客身上獲取更多的利潤，從以往的大眾行銷到現在的目標行銷、直效行銷，都是企業努力的方向。為了將有限的行銷資源發揮到極限，精準的選取目標客戶對企業而言是非常重要的。面對複雜的目標客戶選取之問題，資料探勘是一可行與漸受廣泛應用的有利工具。資料探勘能從資料中找出顯著且有效的消費行為或模式，將能賦予企業更多的經營智慧。

　　本研究以一保險公司(TIC：The Insurance Company)直效行銷資料集為例，期望建立一個目標客戶選取分類模式。首先利用簡易貝氏分類器(naïve bayes classifier)與簡易貝氏分類器結合遺傳演算法(genetic algorithm)，分別找出與顧客回應有關的關鍵屬性欄位群，然後將被選出的關鍵屬性欄位群分別代入類神經網路(neural network)中的倒傳遞網路(back-propagation network，BPN)及支援向量機(support vector machine)建置目標客戶選取分類模式，以找出目標客戶，供業者做參考。

N/A

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三、網站部分：
SQL Server 2005 White Paper
http://www.microsoft.com/sql/2005/techinfo/default.asp
The Insurance Company (TIC) Benchmark
http://www.liacs.nl/~putten/library/cc2000/
Weka
http://www.cs.waikato.ac.nz/ml/weka/