Development of an Intent-Based University Chatbot Using Supervised Learning and NLP Techniques

In the current digital age, chatbots have emerged as essential tools for enhancing communication and providing instant assistance in universities, addressing diverse information needs of students, alumni, and external stakeholders. This paper introduces an intent-based chatbot developed using machine learning techniques, particularly a deep learning feed-forward neural network model. Existing systems often lack accuracy and contextual relevance, resulting in unsatisfactory user experiences. Our approach utilizes a predefined dataset of user intents, applies tokenization and lemmatization, and feeds the processed data into a robustly designed neural network to ensure high accuracy and relevance. This chatbot significantly enhances communication efficiency within university settings and holds promise as an essential tool for fostering engagement among students and other stakeholders.