Systems and Methods for Automated Modeling of Quality for Products and Services Based on Contextual Relevance

A quality assessment system models product or service quality based on contextual relevance. A neural network generates a contextual relevance model that differentiates descriptive characteristics based on a modeled relevance of each descriptive characteristic to the product or service. The system filters reviews based on the contextual relevance model to retain filtered reviews that reference any of the first set of descriptive characteristics. The system generates theme clusters with an encoder. Each theme cluster groups a different subset of the filtered reviews based on an amount of semantic similarity between the different subset of reviews and the theme cluster. The system presents an interface with a first visualization and a second visualization. The first visualization graphically represents a sentiment expressed in reviews grouped to the first theme cluster, and the second visualization graphically represents a sentiment expressed in reviews groups to the second theme cluster.