近年來，企業開始逐漸重視知識管理相關議題，建置其企業內部的知識管理系統。對企業而言，將組織內的知識加以擷取、驗證、儲存、散佈，是企業面對快速變動的環境下，所須具備的必要條件。企業內部對於其知識資產的表達，通常以案例(Cases)或是Lessons的方式，來紀錄企業內對於一個經驗學習、錯誤決策反思、良好的決策方針指引。這些知識案例將隨著時間逐漸累積到達一個龐大的數量，而該知識案例庫將扮演重要的角色—當企業未來面對一個新問題，即可依賴這些既有的知識案例，尋求一個最極為類似之既有知識案例來加以參考，解決現今所面對的新問題，此步驟也正與知識管理循環互相呼應。
過去大部分知識管理系統內的知識案例，其屬性值都以數值為主，而且屬性的選擇，以及表達方式，都是以一種比較僵固的設計方式，來決定出這些案例該用哪些屬性表達與呈現。這些所被選擇出來的屬性，對於該案例內的語意表達，通常明顯不足，抑或沒有非常相關。本研究著重在於將知識案例重新做屬性擷取動作，經由領域專家協助，透過知識擷取分析技術，將領域專家對於該領域問題之重要概念屬性加以擷取與塑模，使其能充分表達該案例內容的語意關係程度。透過此機制，來提升案例搜尋的準確度。基於此種運作機制，知識案例的記載不再侷限於傳統以數值呈現的屬性，對於以較具描述性質的屬性也能夠透過知識擷取技術來處理。
因此，本研究使領域專家透過知識擷取技術，系統化的獲取專家之內隱知識，將其內隱知識加以外顯化，並將該外顯化後之知識結構應用於於知識案例的擷取，同時伴以使用者資訊回饋機制運作，提升知識案例擷取品質。

In recent years, the enterprise gradually places importance on the issue of knowledge management and builds various knowledge management systems to support it. It is a essential condition to retrieval, verify, store and spread knowledge in enterprises for surviving under this fast-changing environment. The enterprise regularly records and stores its knowledge properties in the form of cases or lessons, and relies on the knowledge management system to perform its knowledge management.
Those cases or lessons are accumulated with time, and the knowledge case base plays an important role—finding a most-similar knowledge case for referencing when the enterprise facing a new problem in the feature, this step matches the meaning with the knowledge management.
In the past, the attributes of cases in those systems are mainly in the form of number value, and the choice and expression of attributes are designed inflexibly. Those high-abstracted attributes chosen for cases’ expression are usually insufficient or irrelevant in general. This research emphasizes on re-elicitation of attributes on those knowledge cases, uses knowledge capturing via the support of domain expert, elicits and models the important concepts of domain problems, and makes those concepts can sufficiently express the content of knowledge cases. Through this mechanism, the knowledge management system can improve the accuracy of knowledge cases’ searching, and the expression of cases can use more descriptive attributes instead of traditional attributes by information retrieval.
Therefore, this research transfers domain expert’ implicit knowledge to explicit knowledge structure via knowledge capturing, uses this explicit knowledge structure and user feedback information to improve the query quality of case retrieval.

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