隨著網際網路的廣泛使用，線上互動式自學系統可讓使用者以自己的喜好進行學習，但要讓電腦系統瞭解人類使用的自然語言還是有其困難所在，尤其是中文，首先，中文裡面每個字詞之間並沒有任何區隔符號，第二是因為口語中所使用的句型未必符合正規的文法規則，使得難以去剖析及瞭解使用者真正的語意，第三是要把應用範圍限制在一個特定的領域，否則將太過複雜而難以分析。本論文提出一個互動式回饋機制的自學系統，能剖析並瞭解使用者輸入的自然語言，進而瞭解使用者要學習的內容，對不同的使用者提供客制化的回應內容。 Considering the popularity of the Internet, an automatic interactive feedback system for self-learning websites is becoming increasingly desirable. However, computers still have problems understanding natural languages, especially the Chinese language, firstly because the Chinese language has no space to segment lexical entries (its segmentation method is more difficult than that of English) and secondly because of the lack of a complete grammar in the Chinese language, making parsing more difficult and complicated. Building an automated Chinese feedback system for special application domains could solve these problems. This thesis proposes an interactive feedback mechanism in a self-learning website that can parse, understand and respond to Chinese sentences. This mechanism utilizes a specific lexical database according to the particular application. In this way, self-learning websites can implement a special application domain that chooses the proper response in a user friendly, accurate, and timely manner.
