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Machine Learning-Based Approach For Opinion Mining and Sentiment Polarity Estimation by Cesar H. Gonzalez is a document available to read on EtoBox.

This study presents a machine learning-based product recommendation model that utilizes user reviews to enhance the product selection process and reduce information overload. By analyzing sentiment polarity from a dataset of over 400,000 reviews, the model ranks products based on their cumulative scores and aims to improve customer satisfaction in online shopping. The research highlights the importance of user feedback in recommendation systems and proposes a novel approach to effectively utilize this data

Author

Cesar H. Gonzalez

Language

EN