Designing and development of an Intelligent Chatbot for Enhanced Online Shopping using Natural Language Processing (NLP) techniques

Chatbots have revolutionized the landscape of conversational and voice-assisted technologies, becoming essential tools in modern digital interactions. Leveraging cutting-edge Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques, chatbots are designed to understand user inputs and provide relevant, timely responses. The integration of LLMs represents a substantial leap forward in the sophistication of chatbot interactions. These models, trained on vast and diverse datasets, enable chatbots to generate more human-like, contextually appropriate, and accurate responses. This paper highlights the implementation of various deep learning algorithms and NLP techniques to refine chatbot performance in e-commerce. Techniques such as Named Entity Recognition (NER), sentiment analysis, and context management are pivotal in enhancing the chatbot’s ability to accurately understand and process user inputs. Additionally, reinforcement learning ensures continuous improvement in chatbot interactions by learning from user feedback and evolving.