Enhanced Semantic Question Answering System for e-Learning Environment

To support an automatic assistant learning and self- paced learning mechanism is the objective in today´s e-learning environment. Researches of QA system focus on the following characteristics: understand questioners´ questions in the form of nature language; enhance the accuracy of search result, and establish automatic learning mechanism. Base these characteristics, we develop a Semantic English QA system to analyze learners´ questions and find the relevant answer from the target course ontology. Firstly, this research uses Link Grammar Parser to analyze the syntactic information from the input sentence. According to the syntactic information, secondly, the following process queries the similar word lists generated from WordNet to extend relevant meaning. Thirdly, the two kinds of information can be used to form a semantic tree. Lastly, the semantic tree will map the Data Structure course ontology and find the relevant contents in order to answer learners.