Preserving user-entity differential privacy in natural language modeling
US11816243B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 9, 2021 |
| Grant date | Nov 14, 2023 |
| Priority date | — |
| Expiry date | Feb 8, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems, methods, and non-transitory computer-readable media can generate a natural language model that provides user-entity differential privacy. For example, in one or more embodiments, a system samples sensitive data points from a natural language dataset. Using the sampled sensitive data points, the system determines gradient values corresponding to the natural language model. Further, the system generates noise for the natural language model. The system generates parameters for the natural language model using the gradient values and the noise, facilitating simultaneous protection of the users and sensitive entities associated with the natural language dataset. In some implementations, the system generates the natural language model through an iterative process (e.g., by iteratively modifying the parameters).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.