Utilizing machine learning models for determining an optimized resolution path for an interaction
US10978054B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 3, 2020 |
| Grant date | Apr 13, 2021 |
| Priority date | — |
| Expiry date | Nov 3, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/26
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In some implementations, a device may receive unstructured interaction data identifying an interaction of a user with a user device. The device may receive historical unstructured interaction data identifying historical interactions of users and historical unstructured resolution data identifying historical resolutions to the historical interactions. The device may process the historical unstructured interaction data and the historical unstructured resolution data to determine historical structured interaction data and historical structured resolution data. The device may process the unstructured interaction data and the historical structured interaction data to determine pretext identifiers for the interaction of the user. The device may process the pretext identifiers and the historical structured resolution data to generate a resolution network identifying possible resolutions to the interaction of the user. The device may process the pretext identifiers and the resolution network to determine a resolution path identifying a resolution to the interaction of the user.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.