近年來由於網際網路技術之盛行，資訊需求者需面對越來越多之網路資訊/文件，如何自廣泛資訊中取得使用者真正需要之資訊，同時節省大量資訊過濾與篩選時間，以成為資訊/文件/知識管理之一項重要課題。另一方面，為使資訊需求者快速地瀏覽文件，藉以判斷文件所欲傳達之資訊，即須擷取文件中關鍵詞彙作為文件索引，供資訊需求者參考。傳統資訊管理機制下，文件關鍵字判定工作多以人工方式進行，故需耗費大量人力與時間而無法滿足時效性。因此，本論文首先分析文件內容並擷取各詞彙之出現頻率與位置，根據此兩因子自動建立詞彙關聯關係，並建立詞彙關聯庫。而針對關鍵字擷取議題，本論文乃以詞彙關聯性為基礎，進行各文件關鍵字之自動擷取，且所擷取之關鍵字能適切表達文件內容之重要訊息。最後，發展一詞彙間關聯性為基之文件內容管理模式與系統，以確認模式之可行性，並以一案例評估此模式之有效性。綜合言之，本研究所提出之文件內容管理模式與技術不限於特定應用領域，藉由導入此文件內容管理模式，除可提供企業於知識內容管理議題一可行之解決方案，亦可協助企業累積個人經驗/文件/知識與再利用，方便組織成員利用此架構於網際網路之系統，進行文件資訊擷取、資料集中式儲存、分享與管理。

Abstract

Recently, due to the large amount of electronic information over the Internet, to efficiently retrieve and filter information that meets the user requirements has become an essential issue for enterprise document/knowledge management. In addition, in order to assist users quickly acquire the critical information in the documents, keyword extraction of each document is necessary. Traditionally, document keywords are determined manually and much expertise and time are required. In this research, algorithms for automatic keyword correlation analysis and keyword extraction are proposed. The keyword correlation is analyzed based on the word frequencies and locations of documents in the document repository. Based on the keyword correlation, a recursive approach for document keyword extraction is developed to effectively determine the critical and representative concepts of the target documents. A web-based system for document content management is established and a case study is provided to valuate the proposed model. The proposed approach is not domain-oriented and thus can be applied in different applications. This research is to provide a feasible solution for enterprise knowledge accumulation and reuse in the collaboration networks.

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