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Global Journal of Engineering and Technology Advances
International Peer reviewed Engineering Journal || Crossref DOI || Impact Factor 8.6 || ISSN: 2582-5003

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Research & review articles are invited for publication in September 2026 (Vol. 28, Issue 3) || Submission: up to 28th September || Editorial decision: within 48 hrs.

Implementation of an AI-powered FAQ chatbot using the deep-learning rasa framework

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  • Implementation of an AI-powered FAQ chatbot using the deep-learning rasa framework

Emmanuel Oyerinde, Samuel Abel, Emmanuel Mgbeahuruike, Obumneme Ukandu *, Oluwaseyi⁠ Adediran, Ifeoluwa Ikotun and Mosopefoluwa Adebawojo

Department of Computer Science Babcock University, Nigeria.
 
Research Article
Global Journal of Engineering and Technology Advances, 2025, 23(03), 271-284.
Article DOI: 10.30574/gjeta.2025.23.3.0193
DOI url: https://doi.org/10.30574/gjeta.2025.23.3.0193
Received on 01 May 2025; revised on 16 June 2025; accepted on 19 June 2025
 
Artificial Intelligence (AI) has become more prevalent in our day-to-day activities, as it saves human time and reduces human workload. A lot of students are clueless and know nothing about some concepts of information pertaining to their study period at Babcock University. When most go to the officials for information, it is likely the officials are in one meeting or the other, a long queue is present and many more situations emerge, which then lead to delays in the access of the required information. The aim of this project is to implement an AI-Powered FAQ chatbot using the deep-learning Rasa framework to address critical challenges faced by students seeking timely and accurate information. Based on research, the Rasa Framework was chosen for the development of the FAQ Chatbot. It is an open-source, flexible chatbot framework that allows complete control over the chatbot's behavior. Rasa Framework is known for its deep learning capabilities, specifically in Natural Language Understanding (NLU) and Dialogue Management (DM). The system is a web application with a chat screen to integrate the chatbot model. The chat screen is a user-friendly, graphical interface that the users of the system can interact with. The tools used include: PyCharm, Microsoft Visual Studio, SmartDraw, Draw.io, Flaticon, ExacliDraw.
 
Artificial Intelligence; Chatbot; Rasa; Natural Language Understanding; Dialogue Management
 
https://gjeta.com/sites/default/files/fulltext_pdf/GJETA-2025-0193.pdf

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Emmanuel Oyerinde, Samuel Abel, Emmanuel Mgbeahuruike, Obumneme Ukandu, Oluwaseyi⁠ Adediran, Ifeoluwa Ikotun and Mosopefoluwa Adebawojo. Implementation of an AI-powered FAQ chatbot using the deep-learning rasa framework. Global Journal of Engineering and Technology Advances, 2025, 23(3), 271-284. Article DOI: https://doi.org/10.30574/gjeta.2025.23.3.0193

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