Technique for incremental and flexible detection and modeling of patterns in time series data
US11023350B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 24, 2019 |
| Grant date | Jun 1, 2021 |
| Priority date | — |
| Expiry date | Dec 6, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2201/88
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure describes a flexible technique to learn patterns in time series data that recur over time. The patterns may be used for simulation, predicting future behavior, or detecting anomalies in a system in which the data is collected. The technique incrementally detects daily, weekly, monthly, and yearly patterns. Each pattern is built over time instead of requiring all the data to be available at the beginning of the analysis. Instead of modeling each pattern explicitly, each pattern is described in the context of a day and formed based on time series data collected over an entire day. An example use of the technique is detecting load patterns in a computer system. A metric of system load such as CPU utilization may be collected periodically over a day. The techniques presented herein capture multiple daily models, each representing a different load pattern.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.