Invention Application
- Patent Title: MULTI-SCALE UNSUPERVISED ANOMALY TRANSFORM FOR TIME SERIES DATA
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Application No.: US17074928Application Date: 2020-10-20
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Publication No.: US20220121983A1Publication Date: 2022-04-21
- Inventor: Arun Kumar Jagota
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com, inc.
- Current Assignee: salesforce.com, inc.
- Current Assignee Address: US CA San Francisco
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/23

Abstract:
System receives input value in time series and determines first difference between input value at input time, and first value in time series at input time minus first lag. System determines first score based on first difference and both first average and first dispersion for first lag and time series values. System determines second difference between input value at input time, and second value in timeseries at input time minus second lag. System determines second score based on second difference and both second average and second dispersion for second lag and time series values. System transforms first and second scores into normalized anomaly score in normalized anomaly score time series. Time series database system stores normalized anomaly score time series and input value's time series into time series database. If normalized anomaly score satisfies threshold, system outputs alert including normalized anomaly score and input value retrieved from time series database.
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