Authors : Sowmya A.M; Rakibul Islam Sarkar; Sailesh Singh; Shan Sinha; R.V. Manjunath

Volume/Issue : Volume 9 - 2024, Issue 4 - April

Google Scholar : https://tinyurl.com/mrvwst2x

Scribd : https://tinyurl.com/5exn86bx

DOI : https://doi.org/10.38124/ijisrt/IJISRT24APR1711

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This paper presents the query chatbot system implemented by an institution, which is designed to deliver prompt and efficient responses to inquiries from both students and faculty members. Machine learning algorithms and natural language processing techniques were used in the creation of the chatbot. Using a dataset of commonly asked questions by students, we evaluated the system's functionality. The outcomes showed that the chatbot could deliver precise answers on schedule. The system's ability to provide prompt responses to often- asked questions might potentially save time for both teachers and pupils. Our study demonstrates the value of chatbots in educational environments and suggests avenues for further investigation into this area. A conversational buddy is a piece of software that facilitates online text or voice messaging conversations. They can contextualize human participation, making dialogue more interesting. A powerful tool for building chatbots that can serve as a college inquiry system is the Python framework Rasa X The goal of this research project is to establish guidelines for building a dynamic chatbot that can communicate with users via text and speech.

Keywords : Natural Language Processing Techniques, Institution's Query Chatbot System, Machine Learning Algorithms, Text and Voice Messages, Contextualizing Human Participation, Python Framework, Human-Computer Interaction, Frequently Asked Queries, Construction of a Dynamic Chatbot.

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