Determining a sequential order of types of events based on user actions associated with a third party system

    公开(公告)号:US11188846B1

    公开(公告)日:2021-11-30

    申请号:US16190121

    申请日:2018-11-13

    Applicant: Facebook, Inc.

    Abstract: An online system receives information describing events corresponding to actions associated with a third party system performed by an individual. The received information describes event types and times at which the events occurred. The online system generates nodes of a directed graph associated with the third party system, in which each node corresponds to an event type. For each event, a node count associated with a node corresponding to the event's type is incremented by the online system. Pairs of consecutively occurring events are identified based on times at which the events occurred and an edge describing each transition from one event to another is generated by the online system. The online system determines an edge count for each transition indicating a number of edges describing the transition as well as a sequential order of event types based on one or more node counts and one or more edge counts.

    CROSS-SITE SEMI-ANONYMOUS TRACKING
    3.
    发明申请

    公开(公告)号:US20200336551A1

    公开(公告)日:2020-10-22

    申请号:US16386095

    申请日:2019-04-16

    Applicant: Facebook, Inc.

    Abstract: Semi-anonymous tracking cookies may be utilized to provide relevant content and advertisements to users, while maintaining user privacy. A content publisher may place a tracking cookie on a device. The tracking cookie may include an attribute identifying the cookie as a cross-site semi-anonymous tracking cookie. The device may request anonymization advice for the tracking cookie. An anonymization service may provide anonymization advice for the tracking cookie. The device may store a semi-anonymous value based on the anonymization advice. The semi-anonymous value may be shared by multiple devices. The content publisher may store the actions performed by the multiple devices, without uniquely identifying which device performed the actions. Content and advertisements may be targeted to the device based on the stored actions performed by the multiple devices sharing the semi-anonymous value for the tracking cookie. Additionally, attribution for conversions may be calculated based on the stored actions.

    USER ACTIVITY TRACKING IN THIRD-PARTY ONLINE SYSTEMS

    公开(公告)号:US20190179884A1

    公开(公告)日:2019-06-13

    申请号:US15839738

    申请日:2017-12-12

    Applicant: Facebook, Inc.

    Abstract: Disclosed is a method for identifying an action performed by a user in a third party system. Information associated with a form is received by an online system. For instance, hashed values of a plurality of form fields provided by a user and a description of the plurality of form fields are received by an online system. A form is identified based on the received information. Additionally, a determination whether one or more of the received hashed values correspond to stored values by the online system is made. If the received hashed values correspond to stored values in the online system, a user of the online system is identified based on the stored values corresponding to the one or more received hashed values. An identification of an action associated with the identified form and performed by the user in the third party system is stored.

    Browsing identity
    5.
    发明授权

    公开(公告)号:US11140188B1

    公开(公告)日:2021-10-05

    申请号:US16829511

    申请日:2020-03-25

    Applicant: Facebook, Inc.

    Abstract: An online system determines the likelihood of an interaction between a user and a content item being an invalid interaction. The online system receives an indication of an interaction of a client device with a content item. The online system identifies a device ID for the client device and determines whether the device ID is associated with one or more browser IDs. If the device ID is not associated with any browser ID, the received interaction is likely an invalid interaction. The online system may further determine the likelihood of an online publisher manufacturing interactions. The online system determines a number of invalid interactions and a number of valid interactions associated with the online publisher. The online system determines a ratio between the number of invalid and valid interactions. If the ratio is larger than a threshold value, the online system determines that the online publisher is likely manufacturing interactions.

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