Utilizing machine learning models to generate interactive digital text threads with personalized agent escalation digital text reply options
US11936814B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 22, 2022 |
| Grant date | Mar 19, 2024 |
| Priority date | — |
| Expiry date | Nov 22, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L51/046
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing machine learning models to determine predicted client intent classifications and/or client-agent escalation classes to generate personalized digital text reply options within an automated interactive digital text thread. For example, disclosed systems utilize the machine learning model to generate predicted client-agent escalation classes and corresponding probabilities. The disclosed systems utilize the predicted client-agent escalation classifications and the escalation class probabilities to generate personalized digital text reply options. Moreover, the disclosed systems can provide personalized digital text reply options to a client device within an automated interactive digital text thread, bypassing the inefficiency of menu options or protocols utilized to guide clients to terminal information.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.