Artificial intelligence and/or machine learning models trained to predict user actions based on an embedding of network locations
US11699109B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 28, 2022 |
| Grant date | Jul 11, 2023 |
| Priority date | — |
| Expiry date | Apr 28, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-implemented method can facilitate delivery of targeted content to user devices in situations in which historic tracking data (e.g., cookie data) is generally unavailable and/or unreliable. A p-dimensional embedding of websites can be generated based on a group of user devices for whom tracking data is available. Conversion event data that indicates indicating whether that audience member performed a conversion action can be received. A machine learning model can be trained using the conversion event data and the positions of websites appearing in the conversion event data within the p-dimensional embedding to predict a likelihood of conversion and/or a type of content to provide given a position in the p-dimensional embedding. When an indication that a user device is accessing a website is received, a position of that website in the p-dimensional embedding can be determined and targeted content can be delivered to the user device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.