公开(公告)号：US20200210393A1

公开(公告)日：2020-07-02

申请号：US16569984

申请日：2019-09-13

Applicant: Verint Americas Inc.

Inventor： Ian Roy Beaver ,  Cynthia Freeman ,  Jonathan Merriman

IPC: G06F16/215 ,  G06F16/2458

Abstract: Disclosed are a framework and method for selecting an anomaly detection method for each of a plurality of class of time series based on characteristics a time series example that represents an expected form of data. The method provides classification of a given time series into one of known classes based on expected properties of the time series, filtering the set of possible detection methods based on the time series class, evaluating the remaining detection methods on the given time series using the specific evaluation metric and selecting and returning a recommended anomaly detection method based on the specific evaluation metric.

公开(公告)号：US20230177030A1

公开(公告)日：2023-06-08

申请号：US18103023

申请日：2023-01-30

Applicant: Verint Americas Inc.

Inventor： Ian Roy Beaver ,  Cynthia Freeman ,  Jonathan Merriman

IPC: G06F16/215 ,  G06F16/2458

CPC classification number: G06F16/215 ,  G06F16/2474

Abstract: Disclosed are a framework and method for selecting an anomaly detection method for each of a plurality of class of time series based on characteristics a time series example that represents an expected form of data. The method provides classification of a given time series into one of known classes based on expected properties of the time series, filtering the set of possible detection methods based on the time series class, evaluating the remaining detection methods on the given time series using the specific evaluation metric and selecting and returning a recommended anomaly detection method based on the specific evaluation metric.

公开(公告)号：US12032543B2

公开(公告)日：2024-07-09

申请号：US18103023

申请日：2023-01-30

Applicant: Verint Americas Inc.

Inventor： Ian Roy Beaver ,  Cynthia Freeman ,  Jonathan Merriman

IPC: G06F16/215 ,  G06F16/2458

CPC classification number: G06F16/215 ,  G06F16/2474

Abstract: Disclosed are a framework and method for selecting an anomaly detection method for each of a plurality of class of time series based on characteristics a time series example that represents an expected form of data. The method provides classification of a given time series into one of known classes based on expected properties of the time series, filtering the set of possible detection methods based on the time series class, evaluating the remaining detection methods on the given time series using the specific evaluation metric and selecting and returning a recommended anomaly detection method based on the specific evaluation metric.

公开(公告)号：US11567914B2

公开(公告)日：2023-01-31

申请号：US16569984

申请日：2019-09-13

Applicant: Verint Americas Inc.

Inventor： Ian Roy Beaver ,  Cynthia Freeman ,  Jonathan Merriman

IPC: G06F16/215 ,  G06F16/2458

Abstract: Disclosed are a framework and method for selecting an anomaly detection method for each of a plurality of class of time series based on characteristics a time series example that represents an expected form of data. The method provides classification of a given time series into one of known classes based on expected properties of the time series, filtering the set of possible detection methods based on the time series class, evaluating the remaining detection methods on the given time series using the specific evaluation metric and selecting and returning a recommended anomaly detection method based on the specific evaluation metric.