Design And Implement Of Intelligent Question Answering System In Distance Education

With the popularization of the distance education on Internet, answering questions of distance learning becomes one of the focuses that people pay close attention to. But in distance education, student can't communicate with teacher directly, so it's important that a good distance education system be designed to effectively answer the students' questions and improve learning efficiency. At present, answering systems have many disadvantages such as ignoring query semantic, unsatisfactory searching result, inferior pertinence and validity of answer etc.The domain ontology is a formal, explicit specification of a shared conceptualization, which can represent domain knowledge and facilitate knowledge sharing. The ontology can tag document content and can make it possible to search educational resource based on content in network. The RDF/OWL formal semantic theory provides the foundation for the correct semantic inference on RDF description. This thesis firstly simply introduced the Ontology, and then emphatically discusses the structure of ontology and the semantic query process based on ontology. These technologies provide theoretical foundation for designing and implementing the Intelligent Question Answering system based on Ontology.Based on OWL, the concepts in domain and relations among these concepts, such as inheritance relationship, instance relationship and restrictions, are built by the Ontology to represent highly sharable and reusable domain knowledge. Ontology can be used to describe the semantics of XML data with RDF. The algorithms for computing concept similarity and concept relevance are put forward by this thesis, which can implement intelligent query and adequately mining the background knowledge provided by ontology. Intelligent Question Answering System sets up the knowledge base of courses through teachers' understanding of courses. Answering to students' question is the process of searching the knowledge base for the matched answer. The user can find out the relevant contents with user's requirement in existing resources describing base to implement the relevant information's semantic fusion.