Using machine learning model to make action recommendation to improve performance of client application
US11656969B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 1, 2021 |
| Grant date | May 23, 2023 |
| Priority date | — |
| Expiry date | Dec 1, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F11/3466
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and a method are disclosed for recommending a set of actions to be performed to improve a target performance metric of a client application. An action recommendation system receives the target performance metric from a user associated with the client application. The action recommendation system determines features of the client application describing characteristics and performance history of the client application. The features of the client application and the target performance metric is provided as input to a machine learning model that outputs sets of target features that are likely to result in improvement for the target performance metric. The action recommendation system ranks the sets of target features and selects one of the sets based on the ranking. The action recommendation system determines a set of recommended actions based on the selected set of target features and presents the set of recommended actions to the user.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.