Machine-learning techniques applied to interaction data for determining sequential content and facilitating interactions in online environments
US12361300B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 22, 2021 |
| Grant date | Jul 15, 2025 |
| Priority date | — |
| Expiry date | Feb 2, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/025
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Certain embodiments involve using machine-learning methods to generate a recommendation for sequential content items. A method involves accessing a content item associated with an interaction stage in an online environment. A stage graph, which includes a ratio of interactions, of the content item is generated. An additional content item that includes additional stage-transition content is identified. A sequencing function outcome indicating a portion of the ratio of interactions is determined. A transition probability of receiving an interaction with stage-transition content and an additional interaction with the additional stage-transition content is calculated. A content provider system is caused to provide a recipient device with interactive content that includes the additional content item.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.