Machine-learned database interaction model
US12423721B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 20, 2024 |
| Grant date | Sep 23, 2025 |
| Priority date | — |
| Expiry date | Apr 20, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A central database system trains a machine-learned model based on training data identifying entity characteristics of account holder entities, content item characteristics of a content item presented to the account holder entities, and interactions between the account holder entities and the presented content item. The central database system then identifies a target set of account holder entities, and applies the trained machine-learned model to the entity characteristics of each account holder entity of the target set of account holder entities, the entity characteristics of each of the account holder entities that previously interacted with the content item, and the content item characteristics of the content item to identify a subset of the target set of account holder entities for presentation of the content item. The content item is then displayed to the subset, the content item includes an interface element that, when selected, causes an interaction to take place.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.