Published Paper Details:

This paper is about cross-domain sentiment analysis for product reviews. People write reviews for products like electronics, books, and clothes on websites like Amazon. Sentiment analysis helps to find whether these reviews are positive, negative, or neutral. But sometimes, there are not enough labelled reviews in one domain to train the system. So, cross-domain sentiment analysis uses data from one domain to help another domain. In this paper, a web based system is implemented that collects reviews, processes text using NLP techniques, and classifies the sentiment using machine learning models. This helps to understand customer opinions and improve decision-making for products across different domains. Additionally, the system integrates an AI-powered chatbot that interacts with users in real time, answers queries about products, provides sentiment summaries, and guides customers in exploring product feedback efficiently.