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

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-30
DOI
https://doi.org/10.5281/zenodo.17775803
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

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

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Babcock University (NG)
Openalex Percentile: Top 21%
AI in Service Interactions
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Implementation of an AI-powered FAQ chatbot using the deep-learning rasa framework · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS