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US Patent 10917419 Systems and methods for anomaly detection

Patent 10917419 was granted and assigned to ServiceNow on February, 2021 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
ServiceNow
ServiceNow
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Current Assignee
ServiceNow
ServiceNow
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
109174190
Patent Inventor Names
James Crotinger0
Scott Tucker0
Chinna Babu Polinati0
Date of Patent
February 9, 2021
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Patent Application Number
155878710
Date Filed
May 5, 2017
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Patent Citations
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US Patent 10002203 Service desk data transfer interface
Patent Citations Received
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US Patent 11500411 Formulizing time-series sensor data to facilitate compact storage and eliminate personally identifiable information
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US Patent 11521084 Anomaly detection in a data processing system
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US Patent 11416369 Machine learning models for automated anomaly detection for application infrastructure components
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US Patent 11438212 Fault root cause analysis method and apparatus
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US Patent 11841786 Predictive anomaly detection framework
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US Patent 11930027 Method for evaluating quality of rule-based detections
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US Patent 11940894 Machine learning models for automated anomaly detection for application infrastructure components
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US Patent 12088473 Method, device and system for enhancing predictive classification of anomalous events in a cloud-based application acceleration as a service environment
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...
Patent Primary Examiner
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Kandasamy Thangavelu
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Patent abstract

An anomaly detection module may include a time-series analyzer that classifies current time-series data into at least one of a plurality of classifications based upon historical data and may construct a statistical model representative of the current time-series data based upon the at least one of the plurality of classifications. An anomaly detector monitors a stream of the current time-series data and identifies statistical outliers of the stream of the current time-series data, based upon the statistical model and may determine an anomalous score for the statistical outliers by tracking a history of the statistical outliers; wherein the anomalous score comprises a representation of a magnitude of deviation between the current time-series data and the statistical model over multiple measurements of the current time-series data, over a particular time interval, or both.

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