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    OPTIMIZING APPLICATION PERFORMANCE WITH MACHINE LEARNING
    2.
    发明申请
    OPTIMIZING APPLICATION PERFORMANCE WITH MACHINE LEARNING 有权

    公开(公告)号：US20220308981A1

    公开(公告)日：2022-09-29

    申请号：US17213707

    申请日：2021-03-26

    Applicant: Slack Technologies, Inc.

    Inventor： Jenna Zeigen ,  Natalie Qabazard ,  Anuj Nair ,  Aaron Maurer ,  Yiling Chen

    IPC: G06F11/34 ,  G06N20/00

    Abstract: Media, methods, and systems are disclosed for optimizing performance of a running application in connection with a group-based communication system. Log data is collected regarding prior metrics for applications that have encountered performance events. Application state information is monitored and a machine-learning model mapping application metrics to performance outcomes predicts whether the running application will encounter a performance event. The machine-learning model mapping application metrics to performance outcomes is trained based on the collected logs. Based on whether a degradation outcome will be impactful, an application performance parameter may be degraded.

    USER ACCOUNT TELEMETRY WITHIN A COMMUNICATION PLATFORM
    4.
    发明申请
    USER ACCOUNT TELEMETRY WITHIN A COMMUNICATION PLATFORM 有权

    公开(公告)号：US20210385099A1

    公开(公告)日：2021-12-09

    申请号：US17407891

    申请日：2021-08-20

    Applicant: Slack Technologies, Inc.

    Inventor： Jaime Delanghe ,  Simon Favreau-Lessard ,  Renaud Bourassa-Denis ,  Jenna Zeigen ,  Noah Weiss ,  Jonathan Katzur

    IPC: H04L12/18 ,  H04L29/08 ,  H04L29/06 ,  G06Q10/06

    Abstract: Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products for discovery of individual profile telemetry within a communication platform. The individual profile telemetry may represent an amount and/or frequency of communications between a user and one or more other users of the communication platform. In some examples, the individual profile telemetry may represent an amount of interactions the user has with an object of the communication platform, such as a communication channel, a communication transmitted via the communication channel, a direct messaging instance, or the like. The communication platform may determine the amount and/or frequency of interactions and provide an indication thereof to the user via an interface associated with the communication platform.

    Optimizing application performance with machine learning
    5.
    发明授权
    Optimizing application performance with machine learning 有权

    公开(公告)号：US11620173B2

    公开(公告)日：2023-04-04

    申请号：US17213707

    申请日：2021-03-26

    Applicant: Slack Technologies, Inc.

    Inventor： Jenna Zeigen ,  Natalie Qabazard ,  Anuj Nair ,  Aaron Maurer ,  Yiling Chen

    IPC: G06F11/00 ,  G06F11/34 ,  G06N20/00

    Abstract: Media, methods, and systems are disclosed for optimizing performance of a running application in connection with a group-based communication system. Log data is collected regarding prior metrics for applications that have encountered performance events. Application state information is monitored and a machine-learning model mapping application metrics to performance outcomes predicts whether the running application will encounter a performance event. The machine-learning model mapping application metrics to performance outcomes is trained based on the collected logs. Based on whether a degradation outcome will be impactful, an application performance parameter may be degraded.

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