Systems and methods for automatic apparel wearability model training and prediction
US11068772B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 14, 2019 |
| Grant date | Jul 20, 2021 |
| Priority date | — |
| Expiry date | Feb 14, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0645
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed are methods, systems, and non-transitory computer-readable medium for executing neural network training for dynamically predicting apparel wearability. For example, a method may include generating a training data set comprising one or more historical data attributes of previously shipped apparel, training a neural network based on the training data set to configure one or more trained models to output a metric for any pair of a unique user identifier and a unique apparel identifier, storing one or more trained model objects, collecting prediction data comprising at least one prediction pair including a unique user identifier and a unique apparel identifier, predicting one or more predictive wearability metrics indicative of propensity to wear, dynamically generating one or more match pairs, and determining a match wearability metric for each of the one or more match pairs based on the predicted one or more predictive wearability metrics.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.