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:
Nov. 16, 2021

Filed:

Apr. 18, 2019
Applicant:

Oracle International Corporation, Redwood Shores, CA (US);

Inventors:

Aleksey M. Urmanov, San Diego, CA (US);

Alan Paul Wood, San Jose, CA (US);

Assignee:

Oracle International Corporation, Redwood Shores, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06F 17/16 (2006.01); G06F 16/9035 (2019.01); G06F 16/906 (2019.01);
U.S. Cl.
CPC ...
H04L 63/1425 (2013.01); G06F 16/906 (2019.01); G06F 16/9035 (2019.01); G06F 17/16 (2013.01); H04L 63/0815 (2013.01);
Abstract

The system obtains a multimodal dataset containing different types of data gathered during operation of the computer system, wherein the multimodal dataset includes time-series data for different variables associated with operation of the computer system. Next, the system forms a set of feature groups from the multimodal dataset, wherein each feature group comprises variables from the multimodal dataset containing the same type of data. The system then computes a tripoint similarity matrix for each feature group, and aggregates the tripoint similarity matrices for the feature groups to produce a crossmodal tripoint similarity matrix. Next, the system uses the crossmodal tripoint similarity matrix to cluster the multimodal dataset to form a model. The system then performs prognostic-surveillance operations on real-time multimodal data received from the computer system, wherein the prognostic-surveillance operations use the model as a classifier to detect anomalies. When an anomaly is detected, the system triggers an alert.


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