問題解決之知識支援

Abstract

問題解決為企業創造競爭優勢的一項重要流程。傳統以案例為基礎之推論技術被廣泛地應用在協助工作者解決問題。然而，普遍以案例為基礎之推論技術的處理模式著重在識別類似的問題，卻沒有探索工作者的資訊需求與問題解決流程中狀態的相關情境資訊。而問題解決流程通常是知識密集，因此工作者需要有效的知識支援，以提供必要的資訊用以識別問題發生原因，讓工作者便於針對狀況採取適當的處理動作。在本研究中，我們提出了一個以探勘為基礎之問題解決知識支援系統。基於以案例為基礎之推論與資料探勘技術，系統採用以案例為基礎之推論技術識別類似的狀況與處理動作，並使用文字探勘技術擷取狀態與處理動作之關鍵概念，這些概念將形成設定檔用以建立工作者在處理問題時之資訊需求模式。基於所建立之工作者資訊需求設定檔，有效的知識支援因此可以被提供給工作者相關狀態與處理動作之資訊。此外，關連式規則之探勘技術被應用於問題解決記錄檔中，發掘隱藏的知識樣版。發掘的知識樣版可以識別在狀態與處理動作間經常發生的關連，可以做為輔助決策上的知識，例如，特定狀況下適合的處理動作。我們發展了一個雛形系統以展示工作者在處理問題時，提供相關於狀態、處理動作與決策知識的有效性。此外，基於以案例為基礎之推論、資料探勘技術與規則推論技術，我們採用以案例為基礎之推論技術以識別以情境資訊為基礎之狀態，並依據根據以情境為基礎所建立的工作者資訊需求設定檔，提供相關的知識文件。隱藏的知識樣版被發掘以推論出在狀態特徵與處理動作之間的關連，用以提供以情境為基礎的相關推論知識。最後，我們亦發展了一個雛形系統以展示推論知識的有效性。

Problem-solving is an important process that enables corporations to create competitive business advantages. Traditionally, Case-Based Reasoning (CBR) techniques have been widely used to help workers solve problems. However, conventional approaches focus on identifying similar problems without exploring the information needs of workers and relevant context of situation during the problem-solving process. Such processes are usually knowledge intensive tasks; therefore, workers need effective knowledge support that gives them the information necessary to identify the causes of a problem and enables them to take appropriate action to resolve the situation. In this work, we propose a mining-based knowledge support system for problem-solving. Based on CBR and data mining techniques, in addition to adopting CBR techniques to identify similar situations and the action taken to solve them, the proposed system employs text mining (Automatic Indexing) techniques to extract the key concepts of situations and actions. These concepts form profiles that model workers’ information needs when han-dling problems. Effective knowledge support can thus be facilitated by providing workers with situation/action-relevant information based on the profiles. Moreover, association rule mining is used to discover hidden knowledge patterns from historical problem-solving logs. The dis-covered patterns identify frequent associations between situations and actions, and can there-fore provide decision-making knowledge, i.e., appropriate actions for handling specific situa-tions. We develop a prototype system to demonstrate the effectiveness of providing situa-tion/action relevant information and decision-making knowledge to help workers solve prob-lems. Furthermore, based on CBR, data mining, and rule inference techniques, the con-text-based situation identified by CBR techniques provides effective context-based knowledge documents according to the context-based profile. The hidden knowledge patterns are discov-ered to identify inferred associations between situation features and actions, and can therefore provide context-based relevant knowledge. A prototype system is developed to demonstrate the effectiveness of providing inferred knowledge.