Semantic-extended question answering system for e-learning

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 學位論文 > Item 987654321/34992

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题名:	Semantic-extended question answering system for e-learning
其它题名:	數位學習環境下之語意延伸答問系統
作者:	王文男;Wang, Wen-nan
贡献者:	淡江大學資訊工程學系博士班王英宏;Wang, Ying-hong
关键词:	語意答問系統;Link Grammar;詞彙網路(WordNet);數位學習;Semantic QA;WordNet;Link Grammar
日期:	2007
上传时间:	2010-01-11 05:52:31 (UTC+8)
摘要:	在數位學習環境中，學習者比較容易缺乏同儕與教師間的互動，當遇到課程相關的問題時，往往得不到即時的解決，必須透過線上即時問答系統，或者透過留言版或電子郵件來提出問題；但這必須得仰賴老師或者教學助教即時的在線上提供回應，學習者才能得到解答。如何提供自動化的學習輔助及自我學習機制，則是目前數位學習環境的一個重要發展目標；因此如何設計一個能提供自動化即時回答與教材相關的答問機制，對於學習者的學習成就將會相當助益。因此本論文提出一個支援語意認知方法的答問系統（Semantic QA），採用知識本體技術設計資料結構課程教材，以期能切要回答學習者以自然語言所提問之課程知識。根據上述目標，本論文針對語意分析所採用相關研究方法為：（1）使用Link Grammar Parser來分析學習者所提之問句句法資訊建構句法樹，（2）分析問句類型取得標的片語並建構一個語意樹以表示問句句意，（3）藉由WordNet取得相似字清單以得到更相關的語意資訊，（4）最後將語意樹與課程知識本體比對取得學習者所提問題之答案。而針對於知識本體內容完整性，本論文設計提供知識本體延伸模組分析網路上相關主題之教材，以豐富答問系統知識本體；此外並提供教師回饋機制，教師可藉由此模組觀察系統是否可正確回答學習者問題，並可補充答問系統相關之複合字、問句類型、相似字清單等問句分析的相關資訊。本論文發展的問答系統具備以下特性：（1）瞭解發問者以自然語言形式所提出的問題，（2）增加回答問題的準確率，（3）可以延伸問句分析的相關資訊，(4) 建立自動化的問答系統以輔助學習。 Different from those in the traditional learning, learners in the e-learning environment usually have less opportunity to interact with their teachers or fellows. If learners have questions, they have to seek for answers through the on-line question answering system or post their questions on message board or use e-mail to ask questions. However, teachers or tutors can not solve each question immediately if they are not online simultaneously. Therefore, how to build an automatic assistance for learning and provide a self-paced learning mechanism are the objectives in today’s e-learning environment. For this reason, constructing an automatic question answering mechanism will be very helpful for learners to get solutions instantly. According to the above motivation, this thesis proposes a Semantic-extended Question Answering system (Semantic QA) to analyze learners’ questions and find the relevant answer from the target course ontology which applies the Data Structure to construct teaching materials. To achieve this goal, the following shows the research steps. Firstly, Link Grammar Parser is applied to analyze the Syntactic Information of an input sentence and form a syntactical tree. Secondly, the question type is analyzed to find the target phrase and then form a Semantic Tree to represent the meaning of the question. Thirdly, WordNet is used at this stage to generate the Similar Word Lists to extend relevant meaning. Lastly, the Semantic Tree will be mapped to the Data Structure course ontology and find the relevant contents in order to answer them to learners. The Semantic QA system has the following characteristics: (1) understand learners’ questions in the form of natural language, (2) enhance the accuracy of solutions, (3) make the extensibility of the related question analysis information and (4) establish the automatic learning mechanism.
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