Conversational chat system using attention mechanism for COVID-19 inquiries
Published in International Journal of Intelligent Networks, 2023
Recommended citation: Wang Hui, Nagender Aneja, Sandhya Aneja, Abdul Naim "Conversational chat system using attention mechanism for COVID-19 inquiries." International Journal of Intelligent Networks, 2023. doi: 10.1016/j.ijin.2023.05.003 https://www.sciencedirect.com/science/article/pii/S266660302300012X
(Journal Publication)
Abstract: Conversational artificial intelligence (AI) is an artificial intelligence that uses machine learning techniques to understand and respond to user inputs. This paper presents a conversational chat system that uses an attention mechanism to respond to COVID-19 inquiries. The model is based on the Luong Attention Mechanism’s three scoring methodologies: the Dot Attention Mechanism, the General Attention Mechanism, and the Concat Attention Mechanism. The results show that the accuracy of the dot attention mechanism is highest and is 87% when the test questions were obtained directly from the database, compared to 38% when the attention mechanism is not used. Furthermore, when the questions are asked with natural variations, human verification accuracy is 63% compared to 16% when the attention mechanism is not used.