The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 31, 2023

Filed:

Jul. 30, 2019
Applicant:

Emc Ip Holding Company Llc, Hopkinton, MA (US);

Inventors:

Zachary W. Arnold, Concord, MA (US);

Bina K. Thakkar, Cary, NC (US);

Peter Beale, Acton, MA (US);

Assignee:

EMC IP Holding Company LLC, Hopkinton, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/07 (2006.01); G06F 11/30 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 11/0709 (2013.01); G06F 11/0721 (2013.01); G06F 11/0754 (2013.01); G06F 11/3006 (2013.01); G06F 11/3072 (2013.01);
Abstract

Methods, apparatus, and processor-readable storage media for machine learning-based anomaly detection using time series decomposition are provided herein. An example computer-implemented method includes processing, via machine learning techniques pertaining to time series decomposition functions, a first set of historical time series data derived from multiple systems within an enterprise; generating, based on the processed data, one or more pairs of upper bounds and lower bounds directed to system metrics; identifying system anomalies attributed to one or more of the multiple systems within the enterprise by comparing a second set of historical time series data derived from the one or more systems against the one or more pairs of upper bounds and lower bounds; prioritizing, via machine learning techniques pertaining to weighting functions, the system anomalies; and outputting, in accordance with the prioritization, the system anomalies to a user within the enterprise.


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