Authors:
Rejwan Bin Sulaiman

Addresses:
Department of Computer Science and Technology, Northumbria University, Middlesex Street, London, United Kingdom. 

Abstract:

The use of Artificial Intelligence (AI) and Machine Learning (ML) technologies in customer service has changed a lot in the last few years. The goal of this paper is to create an intelligent chatbot system that enhances company-customer interactions and improves the user experience. The chatbot serves as a virtual assistant, always available to answer client questions and provide logical, context-aware responses, utilising Natural Language Processing (NLP) and Information Retrieval (IR) methods. The research examines diverse chatbot designs, encompassing open- and closed-domain systems with retrieval- and generative-based responses, and evaluates their efficiency and constraints. The suggested system is mostly built on a closed-domain, retrieval-based design. This ensures that answers are accurate and reliable while reducing processing time. This paper also demonstrates how chatbots have evolved, from ELIZA to modern conversational agents like Siri and Alexa. It shows how important they are becoming for automated communication. The system's goal is to bridge the communication gaps that have long existed between businesses and their customers by utilising advanced NLP and machine learning techniques.

Keywords: Machine Learning; Retrieval-Based Response; Generative-Based Response; Information Retrieval; Statistical Machine Translation; Natural Language Processing.

Received on: 13/10/2024, Revised on: 07/01/2025, Accepted on: 01/02/2025, Published on: 05/06/2025

DOI: 10.69888/FTSCS.2025.000436

FMDB Transactions on Sustainable Computing Systems, 2025 Vol. 3 No. 2, Pages: 122-156

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