مرکز منطقه ای اطلاع رساني علوم و فناوري - Semantic Question and Answer System for Distance Education

Abstract :

E-learning and distance education are becoming more popular day by day with the development of web technologies and increase of education demands. Software solutions are accepted more stable than human-powered solutions because of their consistent nature. E-learning and distance education portals overcome time limit for information gaining through benefit of web based communication. Key advantage of e-learning and distance education systems than traditional way is easiness of getting answers for questions. These systems offer learning wherever you are and whenever you want. In order to answer as many questions as possible and benefit from software systems instead of limited manpower, we provide a question answering system through DBpedia ontology. Because of our approach has a flexible architecture, it can be easily ported to other knowledge bases in order to offer domain specific answers. We interpret natural language questions into appropriate SPARQL (SPARQL Protocol And RDF Query Language) queries to be able query over semantic data stores. These previously asked questions are stored in database with answers to be used when same questions are asked in order to improve system performance. With user registration mechanism, students are able to see their own question history and their results. Most of question answering systems used by distance education and e-learning portals are only able to answer questions which their answers are defined before by manually. With our ontology based approach, system is able to answer more questions than before without any human effort. This minimizes human efforts for both system development and maintenance. A natural language question can be asked in different forms despite that they all have same answers. Traditional question answering systems need all of these questions to be defined separately in order to sense this variety. Because of benefiting from both semantic and linguistic analysis, the provided system is able to realize these similarities/differences. Also we provide voice search and answer vocalization to make this system can be used by visually-impaired students. Furthermore this approach also accelerates and eases question answering process. Results and experiments show that proposed system offers better performance and maintenance support than traditional question answering systems.