Jewellery E-Commerce Website With Chatbot

Abstract: This study presents the design and implementation of an intelligent chatbot for a luxury jewellery e-commerce platform. The system employs machine learning techniques to classify customer queries and generate contextually accurate responses. It applies text preprocessing methods such as normalization and feature extraction using vectorization techniques to convert text into numerical form. A deep learning model built with TensorFlow/Keras is used for intent classification, while a regression-based approach supports dynamic jewelry price prediction. The system also integrates fallback mechanisms and heuristic rules to ensure reliability, contextual consistency, and enhanced user interaction quality.

Keywords: Machine Learning, Deep Learning, Intent Classification, Natural Language Processing (NLP), TensorFlow/Keras, TF-IDF Vectorization, Text Preprocessing.