受惠於電腦資訊科技之蓬勃發展、網際網路之普及化，人類擁有更具即時性與便利性之傳輸、溝通與交易環境。在此資訊高速發展的環境中，電子化文件與電子化交易紀錄以幾何級數之速度成長與流通，使網際網路儼然成為一龐大之資料庫。面對此資料庫中數量驚人之資料，如何利用自動化文件分類技術協助企業組織與個體管理電子化文件、以及透過使用者偏好判定技術提供適切之資訊與服務予目標顧客，實為現今相關研究與實務應用之重要議題。
由於電子化文件內容與網頁瀏覽者之網路行為具多樣性與複雜性，若以人工決策判斷文件類型、決定使用者者偏好，其處理速度不僅緩慢且不符合經濟效益，認定標準亦甚難維持一致性。有鑑於此，本論文提出一套智慧型文件與使用者偏好類型判定之模式與技術，此模式之推論作法包含「類別與文件關鍵詞彙之關聯推論」、「文件類型判定」與「使用者偏好類別判定」等主題。其基本理念乃利用企業文件庫中之已知文件與其對應之文件類型，透過關鍵字擷取法則萃取使用者過去所瀏覽網頁或文件之關鍵字頻率；其次，再根據關鍵字頻進行類別與文件關鍵詞彙之關聯推論，推知各關鍵字與文件類型隸屬關係。於文件類別判定與使用者偏好類別判定主題中，首先乃取得使用者所瀏覽之文件紀錄與對應之關鍵字後，以關鍵字-類型隸屬關係進行比對並推得各文件之隸屬係數值；最後，再根據所有累積隸屬係數值推論文件與使用者之類型。
鑑於傳統之自動分類方法多著重於分類正確率與效率性之提升，卻忽略實際分類問題以層級方式反覆進行之特性，本論文乃針對一般分類方法忽略分類深度、分類彈性不足之缺憾，提出一多層級之自動分類方法論，以更符合實際產業應用之需求。整體而言，本論文所提出之自動分類模式可依據使用者之閱讀紀錄推論其偏好趨勢，進而提供企業決策者決定主動行銷對象之參考。此外，其亦可應用於組織之知識管理系統進行文件分類與權限管理，使企業體之知識存取與管理更能發揮實效。

Owing to the drastic development of the information technologies and the popularity of WWW applications, the common users have a more efficient and convenient environment to communicate and exchange information with each other. In the cyberspace, a great number of digital documents and transaction data make the Internet a huge knowledge depository. In order to efficiently manage the various documents and explore the target knowledge users,
automatic document and user classification mechanisms are required for the modern enterprises to provide effective knowledge service.
Automatic classification mechanisms have gradually been developed to reduce the human efforts dedicated to document/user classification. Concerning the high variety of
document contents and user behaviors over the Internet, it is not appropriate for the modern organizations to exploit the document and user characteristics simply by human decision. This thesis develops an approach to automatically and consistently determine the document/user categories according to the document keywords and browse history.
Previously, only the single-level classification approaches of documents and users are concerned. However, the single-level classification mechanisms cannot meet the organization operation requirements. Due to the complexity of enterprise processes,products and services, automatic multi-level classification methodologies of enterprise
documents and users ar e explored in this thesis to fulfill the realization of intelligent document/knowledge management. In order to evaluate the feasibility and effectiveness of the proposed methodologies, a web-based prototype system is developed and a demonstration case is provided. The decision support model as well as the technology aims at providing enterprises an effective classification approach that can be applied in CRM systems for efficient relationship marketing or KM systems for effective document security management.

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