Use of machine-learning models in creating messages for advocacy campaigns
US11316808B1 · kind B1 · utility
Inventors
Key dates
| Filing date | Nov 4, 2021 |
| Grant date | Apr 26, 2022 |
| Priority date | — |
| Expiry date | Nov 4, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An advocacy system uses trained machine learning models to create messages that are sent to advocates or policymakers to achieve desired outcomes for an organization. Desired outcomes can include, for example: an advocate sending a message to a policymaker or legislative representative advocating in favor or the organization's position on an issue; a policymaker acting or voting in favor of the organization's position on an issue; or an advocate making a financial contribution to the organization. The machine learning models can be configured to select possible message characteristics or features that the system will include or use in creating messages for individual senders and recipients. The machine learning models can be trained based on message characteristics, personal profile characteristics of senders/recipients, and outcomes from previously sent messages. Personal profile characteristics of senders/recipients can indicate correlations between certain message characteristics and certain outcomes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.