Authors: Mr. Shashank Tiwari, Kommunuri Ashok Kumar, Valigonda Laxmiprasanna, Kayitha Sai Rachana
Abstract: The Conversational Product Recommendation System using LLM is an AI-driven application designed to enhance product recommendation by enabling natural language interaction between users and the system. In modern e-commerce environments, users often face information overload due to the vast number of available products. Traditional recommendation systems rely on static filtering methods and fail to understand complex user queries expressed in natural language. To address these limitations, the proposed system integrates Large Language Models (LLMs) with Natural Language Processing (NLP) techniques to interpret user intent, preferences, and constraints. The system provides a chatbot-based interface where users can interact conversationally, refine their queries, and receive personalized product recommendations in real time. A recommendation engine processes extracted features and ranks products based on relevance, while a backend database manages product data and user interactions.
