Authors : Ibrahim Mahmoud Ibrahim Alturani and Mohd Pouzi Bin Hamzah
Abstract: Question Answering (QA) systems provide a natural way of requesting specific and concise information from a given data source. A crucial stage of such a system is the information retrieval stage which retrieves the possible passages based on their relevance to the question. Accordingly, this study introduces an approach of knowledge extraction of information retrieval from these corpus based on Conceptual Graph (CG). This study discusses how to enhance the accuracy of text-based QA system by modeling the knowledge automatically by using CGF and answers question semantically. The proposed approach showed efficient results of information retrieval measurement through compare recall and precision with another traditional method that has been applied in this same test collection. The result of experiments produced a score of 0.919 for precision and 0.853 for recall. We evaluate our model and show that for the answering task it performs better than standard QA Model.
Ibrahim Mahmoud Ibrahim Alturani and Mohd Pouzi Bin Hamzah, 2019. An Efficient Semantic Analysis Technique for the Question Answering Systems. Journal of Engineering and Applied Sciences, 14: 8289-8292.