Article
Deep Learning Approach for Sentiment-Driven Rating Prediction
This work presents a web-based application developed to analyze user reviews and predict both sentiment and corresponding star ratings using machine learning and deep learning techniques. The system provides an interactive interface where users can register, log in, upload datasets, and process textual data with ease. After loading the dataset, models such as BERT, LSTM, and a GRU-based approach are trained and evaluated. The application supports both bulk review analysis and single review prediction, making it suitable for different user needs. The output is presented in a clear format, including sentiment labels, predicted ratings, and visual summaries through charts. The results indicate that the system can effectively process textual data and extract meaningful insights from user feedback. Such a system can be applied in areas like e-commerce and customer experience analysis, where understanding user opinion is essential.
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