Developing a Semantic Question Answering System for E-learning Environments using Linguistic Resources

Abstract

The Question answering (QA) system plays a basic role in the acquisition of information and the e-learning environment is considered to be the field that is most in need of the question-answering system to help learners ask questions in natural language and get answers in short periods of time. The main problem in this context is how to understand the questions without any doubts in meaning and how to provide the most relevant answers to the questions. In this study, a question-answering system for specific courses has been developed to support the learning environment. The research outcomes indicate that the proposed method helps to solve the problem of ambiguities in meaning through the integration of natural language processing tools and semantic resources that can help to overcome several problems related to the natural language structure. This method also helps improve the capability to understand students’ needs and, consequently, to retrieve the most suitable answers.