Sentiment Analysis in Product Review

• Technology used: Artificial Intelligence ,Machine Learning ,NLP ,Web development

▪ Data Collection and Labeling: Gather diverse project review dataset with corresponding sentiment labels for robust sentiment analysis model training.

▪ Model Training and Evaluation: Develop sentiment analysis model using ML/NLP techniques and supervised learning algorithms. Evaluate performance using appropriate metrics.

▪ Integration with MongoDB: Connect to MongoDB to store project reviews and sentiment analysis results. Design efficient database schema for data storage.

▪ Real-time Sentiment Analysis: Implement mechanism for real-time sentiment analysis on incoming project reviews, preprocessing text data and applying trained model for sentiment prediction.

▪ Feedback and Iteration: Continuously monitor system performance, gather user feedback, and iteratively refine sentiment analysis model for enhanced accuracy and reliability.