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    Predicting characteristics of users of a third party system that communicates with an online system and determining accuracy of the predicted characteristics
    1.
    发明授权
    Predicting characteristics of users of a third party system that communicates with an online system and determining accuracy of the predicted characteristics 有权

    公开(公告)号：US10311244B2

    公开(公告)日：2019-06-04

    申请号：US15282693

    申请日：2016-09-30

    Applicant: Facebook, Inc.

    Inventor： Weidong Wang ,  Erjie Ang ,  Yongfeng Liu ,  Liang Xu ,  Chaochao Cai

    IPC: G06F21/31 ,  G06F21/62 ,  H04L29/06

    Abstract: An online system maintains characteristics for its users and may access characteristics of users maintained by a third party system. The online system may select content for a user of the third party system based on characteristics maintained by the third party system. If the third party system does not maintain a characteristic for its users, the generates a model predicting the characteristic for third party system users based on a set of online system users identified based on characteristics of third party system users. The online system clusters third party system users based on the predicted characteristic for other third party system users connected to the third party system user. Using verified characteristics for third party system users from a trusted third party system, the online system determines an accuracy of the predicted characteristic for third party system users in a cluster.

    CONTENT SELECTION FOR INCREMENTAL USER RESPONSE LIKELIHOOD
    2.
    发明申请
    CONTENT SELECTION FOR INCREMENTAL USER RESPONSE LIKELIHOOD 审中-公开

    公开(公告)号：US20180150883A1

    公开(公告)日：2018-05-31

    申请号：US15365849

    申请日：2016-11-30

    Applicant: Facebook, Inc.

    Inventor： Joseph Poj Davin ,  William Bullock ,  Erjie Ang

    IPC: G06Q30/02 ,  G06N99/00

    CPC classification number: G06Q30/0269 ,  G06N20/00

    Abstract: An online system provides content items to target users who are identified to have high incremental likelihood of performing conversion actions when presented with content items. The incremental likelihood represents the difference between the response likelihood of performing conversion actions when a content item is presented to a user, and the baseline likelihood when a content item is not presented to the user. The baseline and response likelihood for a user are predicted by one or more machine-learned models. By targeting the content to users that are likely to have a high incremental likelihood, the online system provides content items to users whose conversion actions are more likely to be impacted by the presentation of content items, rather than users that may just be of interest for performing the action.

    DETERMINING EFFECTS OF PRESENTING A CONTENT ITEM TO VARIOUS USERS ON A LIKELIHOOD OF ANOTHER USER PERFORMING A SPECIFIC ACTION ASSOCIATED WITH THE CONTENT ITEM
    3.
    发明申请
    DETERMINING EFFECTS OF PRESENTING A CONTENT ITEM TO VARIOUS USERS ON A LIKELIHOOD OF ANOTHER USER PERFORMING A SPECIFIC ACTION ASSOCIATED WITH THE CONTENT ITEM 审中-公开

    公开(公告)号：US20190019215A1

    公开(公告)日：2019-01-17

    申请号：US15650635

    申请日：2017-07-14

    Applicant: Facebook, Inc.

    Inventor： Erjie Ang ,  Aleksey Sergeyevich Fadeev

    IPC: G06Q30/02 ,  G06F17/30 ,  G06Q30/06

    Abstract: An online system determines a metric indicating whether presenting a content item to various users increased a likelihood of other users performing a specific action associated with the content item. To determine the metric, the online system identifies a control set of users who are not presented with the content item and determines measures of affinity for users of the control set with other users of the control set and for users to whom the content item was presented. Based on measures of affinity for users of the control set and for users who were presented with the content item, the online system identifies segments of users of the control set having different measures of affinity for users of the control set and for users presented with the content item. The online system determines the metric bases on occurrences of the specific action by users in different segments.

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