A Hybrid Deep Learning-Based Intelligent Model for Academic Support Chatbot

Abstract

Chatbots are now widely employed across various applications, especially in systems designed to provide intelligent user support. The chatbots are capable of understanding user requests and delivering appropriate responses promptly and accurately. Traditional systems lack true comprehension and generate results based solely on predefined rules, limiting their use to casual chatting and providing information accessible on the internet. Such systems are inadequate for the specific needs of a college intelligent inquiry system. This work introduces a chatbot system within the educational domain, specifically designed to assist university students with their inquiries. The primary objective is to develop a dedicated architecture, formulate a communication management model, and ensure the delivery of accurate responses to the students. To achieve this, a system is created leveraging Artificial Intelligence (AI) techniques and Natural Language Processing (NLP) to recognize and address any type of query. An experimental campaign is conducted on the implementation of the proposed generative and retrieval-based models to evaluate their feasibility and efficiency. This work explores various chatbot platforms, applications, and potential implementations in college settings, aiming to create a user-friendly and efficient inquiry system.

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