Invention Grant
- Patent Title: Anomaly detection in big data time series analysis
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Application No.: US16708605Application Date: 2019-12-10
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Publication No.: US11645293B2Publication Date: 2023-05-09
- Inventor: Fabrice Pelloin
- Applicant: EXFO Solutions SAS
- Applicant Address: FR Saint-Jacques-de-la-Lande
- Assignee: EXFO SOLUTIONS SAS
- Current Assignee: EXFO SOLUTIONS SAS
- Current Assignee Address: FR Rennes
- Agency: McDonnell Boehnen Hulbert & Berghoff LLP
- Main IPC: G06F16/25
- IPC: G06F16/25 ; G06F16/2458 ; G06N20/00 ; G06F17/14 ; G06F16/23 ; G06F16/182 ; G06N5/04

Abstract:
An example embodiment may involve obtaining training time series data spanning an observation time window and comprising a series of values of a metric at regularly-spaced sample points in time, and analyzing the training time series data to determine one of a periodicity or a pseudo-periodicity across a plurality of consecutive sub-windows, each equal in size to a reference time period and each spanned by the same number N of sample points of metric values. A reference pattern corresponding to a model time series having no anomalies, as well as a reference threshold, may be determined and stored. Runtime time series data may then be obtained and time aligned with the reference pattern. Deviations between the runtime time series and the reference pattern may be identified as anomalies if they exceed the reference threshold. Identified anomalies may be displayed in a display device.
Public/Granted literature
- US20200183946A1 Anomaly Detection in Big Data Time Series Analysis Public/Granted day:2020-06-11
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