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    GENERATING TRACKING URLS AND REDIRECTING FROM TRACKING URLS
    2.
    发明申请
    GENERATING TRACKING URLS AND REDIRECTING FROM TRACKING URLS 审中-公开

    公开(公告)号：US20200027128A1

    公开(公告)日：2020-01-23

    申请号：US16584728

    申请日：2019-09-26

    Applicant: Oracle International Corporation

    Inventor： Michael J. Strutton ,  Steven Keith Woods ,  Chad Estes ,  Kimberly Ann Wolfe ,  Donald Chun Wing Ho ,  Yizhou Jiang ,  Natalie You ,  Wenhua Li

    IPC: G06Q30/02

    Abstract: A single tracking URL collects tracking information for multiple tracking services based on multiple tracking URL templates. A dynamic link generator generates a tracking URL configured to collect tracking information requested by each of a set of enabled tracking URL templates. The tracking information is transmitted to the tracking services associated with the enabled tracking URL templates. Additionally or alternatively, a tracking URL is configured to redirect a consumer to one of a candidate set of destination URLs. A tracking URL includes a base URL, which is resolved to an IP address of a server of a particular tracking service. Based on tracking data associated with the tracking URL and/or digital body language associated with the consumer, the particular tracking service selects one of a candidate set of destination URLs associated with the tracking URL. A destination page corresponding to the selected destination URL is presented to the consumer.

    Generating tracking URLs and redirecting from tracking URLs
    4.
    发明授权
    Generating tracking URLs and redirecting from tracking URLs 有权

    公开(公告)号：US11704696B2

    公开(公告)日：2023-07-18

    申请号：US16584728

    申请日：2019-09-26

    Applicant: Oracle International Corporation

    Inventor： Michael J. Strutton ,  Steven Keith Woods ,  Chad Estes ,  Kimberly Ann Wolfe ,  Donald Chun Wing Ho ,  Yizhou Jiang ,  Natalie You ,  Wenhua Li

    IPC: G06Q30/0251

    CPC classification number: G06Q30/0261 ,  G06Q30/0267

    Abstract: A single tracking URL collects tracking information for multiple tracking services based on multiple tracking URL templates. A dynamic link generator generates a tracking URL configured to collect tracking information requested by each of a set of enabled tracking URL templates. The tracking information is transmitted to the tracking services associated with the enabled tracking URL templates. Additionally or alternatively, a tracking URL is configured to redirect a consumer to one of a candidate set of destination URLs. A tracking URL includes a base URL, which is resolved to an IP address of a server of a particular tracking service. Based on tracking data associated with the tracking URL and/or digital body language associated with the consumer, the particular tracking service selects one of a candidate set of destination URLs associated with the tracking URL. A destination page corresponding to the selected destination URL is presented to the consumer.

    Machine learning system for configuring social media campaigns
    5.
    发明授权
    Machine learning system for configuring social media campaigns 有权

    公开(公告)号：US11093979B2

    公开(公告)日：2021-08-17

    申请号：US16239057

    申请日：2019-01-03

    Applicant: Oracle International Corporation

    Inventor： Michael J. Strutton ,  John B. Nolt ,  Chad Estes ,  Kimberly Ann Wolfe ,  Yizhou Jiang ,  Natalie You ,  Wenhua Li ,  Tara U. Roberts

    IPC: G06Q30/02 ,  G06N20/00 ,  G06Q50/00 ,  G06K9/62 ,  H04L12/58 ,  G06K9/66

    Abstract: Techniques for using machine learning to configure social media campaigns are disclosed. A social relationship management (SRM) service performs supervised machine learning to generate a learned model, at least by: generating feature vectors based on training data including campaign configuration data and one or more campaign success metrics; and performing pattern recognition on the feature vectors to determine one or more preferred campaign configurations. The SRM service publishes messages to one or more social media platforms and receives user interaction data associated with users' interactions with the messages. The SRM service performs unsupervised machine learning to update the learned model based at least in part on the user interaction data. The SRM service receives a request to configure a social media campaign, applies data associated with the request to the learned model to determine a preferred campaign configuration, and configures the social media campaign based on the preferred campaign configuration.

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