MACHINE LEARNING BASED IDENTIFICATION OF BROKEN NETWORK CONNECTIONS

    公开(公告)号:US20190197077A1

    公开(公告)日:2019-06-27

    申请号:US15318229

    申请日:2016-10-17

    Applicant: GOOGLE LLC

    Inventor: Xin Li Fang Yang

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying broken network connections. In one aspect, a system includes front-end server(s) that receive data specifying, for multiple different user interactions with one or more application links that link to a given application, presentation durations specifying how long application content linked to by the application link was presented following the multiple different user interactions with the application link(s). Back-end server(s) that communicate with the front end server(s) can classify each application link as broken or working based on application of a machine learning model to the presentation durations for the application link. The machine learning model can be generated using labeled training data. The back-end server(s) can generate and output an alert identifying an application link as a broken link based on the application link being classified as broken by the machine learning model.

    Machine learning classification of an application link as broken or working

    公开(公告)号:US11361046B2

    公开(公告)日:2022-06-14

    申请号:US16798019

    申请日:2020-02-21

    Applicant: Google LLC

    Inventor: Xin Li Fang Yang

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying broken network connections. In one aspect, a system includes front-end server(s) that receive data specifying, for multiple different user interactions with one or more application links that link to a given application, presentation durations specifying how long application content linked to by the application link was presented following the multiple different user interactions with the application link(s). Back-end server(s) that communicate with the front end server(s) can classify each application link as broken or working based on application of a machine learning model to the presentation durations for the application link. The machine learning model can be generated using labeled training data. The back-end server(s) can generate and output an alert identifying an application link as a broken link based on the application link being classified as broken by the machine learning model.

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