Graph-based prediction for contact suggestion in a location sharing system

    公开(公告)号:US11868414B1

    公开(公告)日:2024-01-09

    申请号:US16353604

    申请日:2019-03-14

    Applicant: Snap Inc.

    CPC classification number: G06F16/9535 G06N20/00 G06F3/0484 G06N3/08

    Abstract: Methods, systems, and devices for generating contact suggestions for a user of a social network. A first score is computed for each one of the plurality of users, the first score being computed using an edge-weighted ranking algorithm based on the user graph. A second score is computed, using a machine learning model, for each user of the plurality of users, the second score of each user being, at least partially, based on the first score of said user, with the second score of each user being representative of a probability of a first user sending a connection request to said user. A ranked contact suggestion list of one or more users of the plurality of users is generated, the one or more users being ranked based on their respective second score.

    GRAPH-BASED PREDICTION FOR CONTACT SUGGESTION IN A LOCATION SHARING SYSTEM

    公开(公告)号:US20230385347A1

    公开(公告)日:2023-11-30

    申请号:US18450110

    申请日:2023-08-15

    Applicant: Snap Inc.

    CPC classification number: G06F16/9535 G06N20/00 G06F3/0484

    Abstract: Methods, systems, and devices for generating contact suggestions for a user of a social network. A first score is computed for each one of the plurality of users, the first score being computed using an edge-weighted ranking algorithm based on the user graph. A second score is computed, using a machine learning model, for each user of the plurality of users, the second score of each user being, at least partially, based on the first score of said user, with the second score of each user being representative of a probability of a first user sending a connection request to said user. A ranked contact suggestion list of one or more users of the plurality of users is generated, the one or more users being ranked based on their respective second score.

    Sleep detection in a location sharing system

    公开(公告)号:US10936066B1

    公开(公告)日:2021-03-02

    申请号:US16274891

    申请日:2019-02-13

    Applicant: Snap Inc.

    Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.

    Sleep detection in a location sharing system

    公开(公告)号:US10725542B1

    公开(公告)日:2020-07-28

    申请号:US16274891

    申请日:2019-02-13

    Applicant: Snap Inc.

    Abstract: Methods, systems, and devices for predicting a state of a user (e.g., asleep or awake). In some embodiments, the location sharing system accesses historical activity data of the user and extracts historical sleep records from the historical activity data. The system clusters the historical sleep records into a plurality of clusters and extracts a sleep pattern from each one of the plurality of clusters. Then, when the location sharing system receives current activity data of the user, the system can predict whether the user is currently asleep based on the current activity of the user and at least one of the sleep patterns. Some embodiments additionally compute an estimated wake up time of the user. Some embodiments share the predicted physiological state of the user with the user's friends via the map GUI. Some embodiments additionally share the estimated wake up time of the user.

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