Cross-category item associations using machine learning
US11037071B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 6, 2017 |
| Grant date | Jun 15, 2021 |
| Priority date | — |
| Expiry date | Feb 21, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0643
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning engine may be used to identify items in a second item category that have a visual appearance similar to the visual appearance of a first item selected from a first item category. Image data and text data associated with a large number of items from different item categories may be processed and used by an association model created by a machine learning engine. The association model may extract item attributes from the image data and text data of the first item. The machine learning engine may determine weights for parameter types, and the weights may calibrate the influence of the respective parameter types on the search results. The association model may be deployed to identify items from different item categories that have a visual appearance similar to the first item. The association model may be updated over time by the machine learning engine as data correlations evolve.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.