在這個競爭激烈的時代，企業為了掌握競爭優勢，時時都得注意最新資訊，這些資訊也許在報章媒體上、也許在市場中、也許就存在企業自己的資料庫中。如何將這些隱藏的資訊挖掘出來進而轉換成有用的競爭策略，是資料探勘這個領域的主題。
顧客關係管理(CRM)系統是近來最常被談論的資料探勘應用之一，本研究分析一3C零售業者的顧客管理系統中的一個子系統----聯名卡推薦系統，並提出一個漸進式資料探勘分類系統的架構，應用此系統架構到此聯名卡推薦系統上，與原先系統所使用的方法比較，研究此系統架構應用在相關問題時是否能得到較佳的效果。經過本研究實驗發現這樣的架構確能達到預期加速的目的，而且所建造出來的分類模型和原系統兩者間的準確率差異在可接受的範圍內。

In this high competition age, a company has to continuously keep an eye on the latest information in order to hold the upper hand of the industry. The company may have to find the information on the mass media or on the market. They can even find useful information in their own database. The task of mining unseen information and then transforming it into the competitive strategy is essential in the data mining area.
Customer relationship management system is one of the most popular data mining applications. In this study, we analyze a subsystem of a 3C retailer’s CRM System ---an eCard recommendation system. At the same time, we propose an architecture for incremental data classification. We then apply this technique to the eCard recommendation system to see whether it would perform better than the existing ones. Experimental results show that the classifier built according to the proposed method has acceptable error rate compared with the existing classifiers. Moreover, it can generate a set of rules which provide some high level semantic description about the data.

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