This document discusses the natural language processing and machine learning techniques used to analyze product reviews and extract opinion phrases. It describes using tools like NLTK, scikit-learn, Stanford sentiment library, Apache Storm, and PostgreSQL to process review data, cleanse it, augment it with part-of-speech tags, extract features, and store the results in a database for visualization with D3.js. The overall process involves data processing with Apache Storm, feature extraction using part-of-speech tagging and chunking, and storing the output in a database for reporting and visualization.