Patent · US Active

Graph convolutional anomaly detection

US11494787B2 · kind B2 · utility

48Cited by

2References

20Claims

0Family size

Assignee

Optum, Inc. · US

Inventors

Parker J. Erickson · Plymouth, US
Gerald Liu · Maple Grove, US
Rex Shen · Eden Prairie, US
Devin Uner · Carpentersville, US
George Williams · Austin, US
Zachary Babcock · Elk River, US
Lydia M. Narum · St. Louis Park, US

Key dates

Filing date	Jun 30, 2020
Grant date	Nov 8, 2022
Priority date	—
Expiry date	Apr 28, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG06Q40/08
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

There is a need for more effective and efficient anomaly detection. This need can be addressed by, for example, solutions for performing/executing graph convolutional anomaly detection. In one example, a method includes identifying related graph database input data associated with a predictive entity; generating related graph feature data for the predictive entity; generating, based on the related graph feature data and using a graph convolutional neural network model, an anomaly detection score for the predictive entity, wherein at least a portion of the graph convolutional neural network model is trained using confirmation feedback data; performing an anomaly confirmation to generate the confirmation feedback data object for the predictive entity, and integrating the confirmation feedback data object for the predictive entity into the confirmation feedback data associated with the graph convolutional anomaly detection.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.