Detecting anomalies during operation of a computer system based on multimodal data

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United States of America Patent

PATENT NO 11178161
APP PUB NO 20200336500A1
SERIAL NO

16388057

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Abstract

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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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Patent Owner(s)

  • ORACLE INTERNATIONAL CORPORATION

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Urmanov, Aleksey M San Diego, US 110 1194
Wood, Alan Paul San Jose, US 14 196

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