JNEC Q-BOT: A Rule-Based Chatbot for Enhancing Student Services and Institutional Accessibility

Abstract

In this 21st century, with all the digitalization, universities face challenges in handling the same repeated questions from visitors, freshmen, and current students regarding admission, fee structures, courses, and campus facilities. This project introduces a rule-based college inquiry chatbot, which aims to provide 24/7 automated responses to frequently asked questions, thereby reducing administrative workload. The chatbot is built using the Rasa framework and follows a rule-based architecture, where user questions are processed and matched with predefined intents to give responses stored in files (nlu.yml, domain.yml). The chatbot provides instant, accurate, and context aware answers using a rule-based NLU approach without relying on machine learning. This chatbot has the capability to curl information based on different college services and activities through simple, human-like conversations. It helps tackle problems and offers scalable solutions for providing quick services to users through a conversational interface.