公开(公告)号：US11928017B2

公开(公告)日：2024-03-12

申请号：US17664409

申请日：2022-05-21

Applicant: Google LLC

Inventor： Zichuan Ye ,  Jiashang Liu ,  Forest Elliott ,  Amir Hormati ,  Xi Cheng ,  Mingge Deng

IPC: G06F11/07

CPC classification number: G06F11/0793 ,  G06F11/0709 ,  G06F11/079

Abstract: A method includes receiving a point data anomaly detection query from a user. The query requests the data processing hardware to determine a quantity of anomalous point data values in a set of point data values. The method includes training a model using the set of point data values. For at least one respective point data value in the set of point data values, the method includes determining, using the trained model, a variance value for the respective point data value and determining that the variance value satisfies a threshold value. Based on the variance value satisfying the threshold value, the method includes determining that the respective point data value is an anomalous point data value. The method includes reporting the determined anomalous point data value to the user.

公开(公告)号：US20240193035A1

公开(公告)日：2024-06-13

申请号：US18438717

申请日：2024-02-12

Applicant: Google LLC

Inventor： Zichuan Ye ,  Jiashang Liu ,  Forest Elliott ,  Amir Hormati ,  Xi Cheng ,  Mingge Deng

IPC: G06F11/07

CPC classification number: G06F11/0793 ,  G06F11/0709 ,  G06F11/079

Abstract: A method includes receiving a point data anomaly detection query from a user. The query requests the data processing hardware to determine a quantity of anomalous point data values in a set of point data values. The method includes training a model using the set of point data values. For at least one respective point data value in the set of point data values, the method includes determining, using the trained model, a variance value for the respective point data value and determining that the variance value satisfies a threshold value. Based on the variance value satisfying the threshold value, the method includes determining that the respective point data value includes an anomalous point data value. The method includes reporting the determined anomalous point data value to the user.

公开(公告)号：US20230153311A1

公开(公告)日：2023-05-18

申请号：US18053738

申请日：2022-11-08

Applicant: Google LLC

Inventor： Xi Cheng ,  Zichuan Ye ,  Peng Lin ,  Jiashang Liu ,  Amir Hormati ,  Mingge Deng

IPC: G06F16/2458 ,  G06F16/215 ,  G06F16/25

CPC classification number: G06F16/2462 ,  G06F16/215 ,  G06F16/256

Abstract: A method for anomaly detection includes receiving an anomaly detection query from a user. The anomaly detection query requests data processing hardware determine one or more anomalies in a dataset including a plurality of examples. Each example in the plurality of examples is associated with one or more features. The method includes training a model using the dataset. The trained model is configured to use a local outlier factor (LOF) algorithm. For each respective example of the plurality of examples in the dataset, the method includes determining, using the trained model, a respective local deviation score based on the one or more features. The method includes determining that the respective local deviation score satisfies a deviation score threshold and, based on the location deviation score satisfying the threshold, determining that the respective example is anomalous. The method includes reporting the respective anomalous example to the user.