Well Being Assistance Chat Application
DOI:
https://doi.org/10.47392/irjash.2023.S066Keywords:
Chatbot, Natural Language Processing, Client Server Architecture, Tokenization, LemmatizationAbstract
Nowadays chatbots are widely used by almost every ecommerce, commercial and public welfare website to provide an intellectually rapid solution to customers. It provides extensive range of solutions from customer service to suggesting sales options, providing better service and customer satisfaction. Ever since the introduction of first Chabot, technological developments in the field of Artificial Intelligence has lead to tremendous advancements in designing chatbots that can efficiently mimic human conversations. This paper presents implementation of a chatbot for providing wellbeing assistance to the users. Wellbeing assistance chatbot not only offers effortless assistance to frequent enquiries of the users but additionally indicates the gravity of medical situation to the user. It can converse with people about their health condition and prescribe medications for common sickness. It can be deployed in hospitals for efficiently reducing overcrowding of the patients. Accuracy of the working model can be further increased by creating and using real time demographic data to train the model even after deployment. The proposed wellbeing assistance Chabot is based on Natural language processing (NLP), client server architecture, neural network and server to generate reports.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.