Systems and methods for detecting long term seasons
US12001926B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 23, 2018 |
| Grant date | Jun 4, 2024 |
| Priority date | — |
| Expiry date | Sep 13, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for machine-learning of long-term seasonal patterns are disclosed. In some embodiments, a network service receives a set of time-series data that tracks metric values of at least one computing resource over time. Responsive to receiving the time-series data, the network service detects a subset of metric values that are outliers and associated with a plurality of timestamps. The network service maps the plurality of timestamps to one or more encodings of at least one encoding space that defines a plurality of encodings for different seasonal patterns. Based on the mapped encodings, the network service generates a representation of a seasonal pattern. Based on the representation of the seasonal pattern, the network service may perform one or more operations in association with the at least one computing resource.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.