Product metrics monitoring and anomaly detection using machine learning models
US12348793B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 28, 2022 |
| Grant date | Jul 1, 2025 |
| Priority date | — |
| Expiry date | Jan 3, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N21/466
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A method may include determining a combination of values of attributes represented by reference data associated with computing devices by training a machine learning model based on an association between (i) respective values of the attributes and (ii) the computing devices entering a device state. The combination may be correlated with entry into the device state. The method may also include selecting a subset of the computing devices that is associated with the combination of values. The method may additionally include determining a first rate at which computing devices of the subset have entered the device state during a first time period and a second rate at which one or more computing devices associated with the combination have entered the device state during a second time period, and generating an indication that the two rates differ.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.