Application digital content control using an embedded machine learning module
US11243747B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 31, 2020 |
| Grant date | Feb 8, 2022 |
| Priority date | — |
| Expiry date | Aug 31, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Application personalization techniques and systems are described that leverage an embedded machine learning module to preserve a user's privacy while still supporting rich personalization with improved accuracy and efficiency of use of computational resources over conventional techniques and systems. The machine learning module, for instance, may be embedded as part of an application to execute within a context of the application to learn user preferences to train a model using machine learning. This model is then used within the context of execution of the application to personalize the application, such as control access to digital content, make recommendations, control which items of digital marketing content are exposed to a user via the application, and so on.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.