Question Answering Systems Employing Artificial Intelligence Techniques

Nowadays, the majority of users try to move in the right direction for information that is available over the internet. A question-answering system that can grasp the user’s natural language query and offer a prompt, accurate response is therefore necessary. In this paper, question answering system that employs a variety of approaches, namely a QA system has been reviewed that provides responses for a variety of question kinds and on a domain basis. In addition to this, the study draws attention to the gaps that were found in the previously published research. Reviewing the different working systems in the medical sector, namely HONQA, EAGLi, and askHERMES, revealed that HONQA delivers a one-line solution for the inquiry, however with EAGLi, we need to validate the answer that was provided by it. askHERMES provides an answer that is needed to be validated. In the healthcare industry, the askHERMES question and answer platform is by far the most popular and widely used option. In contrast, all of the responses that EAGLi provides are to inquiries of the definition types of questions.