Framework for the automated determination of classes and anomaly detection methods for time series
US12032543B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 30, 2023 |
| Grant date | Jul 9, 2024 |
| Priority date | — |
| Expiry date | Jan 30, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/2474
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed are a framework and method for selecting an anomaly detection method for each of a plurality of class of time series based on characteristics a time series example that represents an expected form of data. The method provides classification of a given time series into one of known classes based on expected properties of the time series, filtering the set of possible detection methods based on the time series class, evaluating the remaining detection methods on the given time series using the specific evaluation metric and selecting and returning a recommended anomaly detection method based on the specific evaluation metric.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.