Visualization Of High-Dimensional Data

    公开(公告)号:US20210264304A1

    公开(公告)日:2021-08-26

    申请号:US17318408

    申请日:2021-05-12

    Applicant: eBay Inc.

    Abstract: A system is configured to detect a small, but meaningful, anomaly within one or more metrics associated with a platform. The system displays visuals of the metrics so that a user monitoring the platform can effectively notice a problem associated with the anomaly and take appropriate action to remediate the problem. A first visual includes a radar-based visual that renders an object representing data for a set of metrics being monitored. A second visual includes a tree map visual that includes sections where each section is associated with an attribute used to compose the set of metrics. Via the display of the visuals, the techniques provide an improved way of representing a large number of metrics (e.g., hundreds, thousands, etc.) being monitored for a platform. Moreover, the techniques are configured to expose useful information associated with the platform in a manner that can be effectively interpreted by a user.

    Cross-correlation of metrics for anomaly root cause identification

    公开(公告)号:US11886285B2

    公开(公告)日:2024-01-30

    申请号:US17843198

    申请日:2022-06-17

    Applicant: eBay Inc.

    CPC classification number: G06F11/0793 G06F11/0706

    Abstract: Technologies are disclosed herein for cross-correlating metrics for anomaly root cause detection. Primary and secondary metrics associated with an anomaly are cross-correlated by first using the derivative of an interpolant of data points of the primary metric to identify a time window for analysis. Impact scores for the secondary metrics can be then be generated by computing the standard deviation of a derivative of data points of the secondary metrics during the identified time window. The impact scores can be utilized to collect data relating to the secondary metrics most likely to have caused the anomaly. Remedial action can then be taken based upon the collected data in order to address the root cause of the anomaly.

    Visualization of high-dimensional data

    公开(公告)号:US11593682B2

    公开(公告)日:2023-02-28

    申请号:US17318408

    申请日:2021-05-12

    Applicant: eBay Inc.

    Abstract: A system is configured to detect a small, but meaningful, anomaly within one or more metrics associated with a platform. The system displays visuals of the metrics so that a user monitoring the platform can effectively notice a problem associated with the anomaly and take appropriate action to remediate the problem. A first visual includes a radar-based visual that renders an object representing data for a set of metrics being monitored. A second visual includes a tree map visual that includes sections where each section is associated with an attribute used to compose the set of metrics. Via the display of the visuals, the techniques provide an improved way of representing a large number of metrics (e.g., hundreds, thousands, etc.) being monitored for a platform. Moreover, the techniques are configured to expose useful information associated with the platform in a manner that can be effectively interpreted by a user.

    Visualization of high-dimensional data

    公开(公告)号:US11036607B2

    公开(公告)日:2021-06-15

    申请号:US16745792

    申请日:2020-01-17

    Applicant: eBay Inc.

    Abstract: A system is configured to detect a small, but meaningful, anomaly within one or more metrics associated with a platform. The system displays visuals of the metrics so that a user monitoring the platform can effectively notice a problem associated with the anomaly and take appropriate action to remediate the problem. A first visual includes a radar-based visual that renders an object representing data for a set of metrics being monitored. A second visual includes a tree map visual that includes sections where each section is associated with an attribute used to compose the set of metrics. Via the display of the visuals, the techniques provide an improved way of representing a large number of metrics (e.g., hundreds, thousands, etc.) being monitored for a platform. Moreover, the techniques are configured to expose useful information associated with the platform in a manner that can be effectively interpreted by a user.

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