US 2026/0220431 A1 · ANOMALY DETECTION IN TIME-SERIES DATA

Abstract

Example implementations related to automated anomaly detection in time-series datasets are disclosed. In an example, a request for an automated redemption operation is received. The request includes a plurality of time-series data elements. A reconstruction error is generated for the request using a trained autoencoder model that receives the plurality of time-series data elements. The reconstruction error is representative of a difference between the plurality of time-series data elements and a reconstructed plurality of time-series data elements generated by the trained autoencoder model. In response to determining the reconstruction error is above the predetermined threshold and that the request for the automated redemption operation satisfies at least one anomaly detection rule, execution of the automated redemption operation is prevented.

Claims20

Dependent claims

A system, comprising:

a processor;
and
a non-transitory memory storing instructions that, when executed, cause the processor to:
receive a request for an automated redemption operation, wherein the request includes a plurality of time-series data elements;
generate a reconstruction error for the request for the automated redemption operation using a trained autoencoder model that receives the plurality of time-series data elements, wherein the reconstruction error is representative of a difference between the plurality of time-series data elements and a reconstructed plurality of time-series data elements generated by the trained autoencoder model;
determine whether the reconstruction error is above a predetermined threshold;
in response to determining the reconstruction error is above the predetermined threshold, determine whether the request for the automated redemption operation satisfies at least one anomaly detection rule;
and
in response to determining the request for the automated redemption operation satisfies the at least one anomaly detection rule, prevent execution of the automated redemption operation.

6 more elements

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause a device to perform operations comprising:

receiving a request for an automated redemption operation, wherein the request includes a plurality of time-series data elements;
generating a reconstruction error for the request for the automated redemption operation using a trained autoencoder model that receives the plurality of time-series data elements, wherein the reconstruction error is representative of a difference between the plurality of time-series data elements and a reconstructed plurality of time-series data elements generated by the trained autoencoder model;
determining whether the reconstruction error is above a predetermined threshold;
in response to determining the reconstruction error is above the predetermined threshold, determining whether the request for the automated redemption operation satisfies at least one anomaly detection rule;
and
in response to determining the request for the automated redemption operation satisfies the at least one anomaly detection rule, preventing execution of the automated redemption operation.

3 more elements

Dependencies are inferred from the claim text.

Anomaly detection in time-series data

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Anomaly detection in time-series data

Life of this patent

Abstract

Claims20