Feature-based data retrieval

Feature-based data retrieval is a method used to find relevant data by focusing on specific characteristics or attributes—called features—of the data, such as color, shape, or texture. Instead of comparing raw data directly, the system analyzes these features to quickly identify items that match criteria or are similar to a query. This approach makes searching more efficient, especially with large datasets, by filtering and comparing key attributes rather than entire data points. It's commonly used in image search, recommendation systems, or pattern recognition, enabling faster and more accurate retrieval based on meaningful data properties.