Generating personalized in-application recommendations utilizing in-application behavior and intent

    公开(公告)号:US12061916B2

    公开(公告)日:2024-08-13

    申请号:US17657477

    申请日:2022-03-31

    Applicant: Adobe Inc.

    CPC classification number: G06F9/451

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that recommends application features of software applications based on in-application behavior and provides the recommendations within a dynamically updating graphical user interface. For instance, in one or more embodiments, the disclosed systems utilize behavioral signals reflecting the behavior of a user with respect to one or more software applications to recommend application features of the software application(s). For instance, in some cases, the disclosed systems recommend an application feature related to recent activity user, an application feature from a curated recommendation list that has yet to be viewed, and/or an application feature determined via machine learning. In some embodiments, the disclosed systems dynamically update a graphical user interface of a client device in real time as the user utilizes the client device to access and navigate the software application(s) to display these recommendations.

    GENERATING PERSONALIZED IN-APPLICATION RECOMMENDATIONS UTILIZING IN-APPLICATION BEHAVIOR AND INTENT

    公开(公告)号:US20230315491A1

    公开(公告)日:2023-10-05

    申请号:US17657477

    申请日:2022-03-31

    Applicant: Adobe Inc.

    CPC classification number: G06F9/451

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that recommends application features of software applications based on in-application behavior and provides the recommendations within a dynamically updating graphical user interface. For instance, in one or more embodiments, the disclosed systems utilize behavioral signals reflecting the behavior of a user with respect to one or more software applications to recommend application features of the software application(s). For instance, in some cases, the disclosed systems recommend an application feature related to recent activity user, an application feature from a curated recommendation list that has yet to be viewed, and/or an application feature determined via machine learning. In some embodiments, the disclosed systems dynamically update a graphical user interface of a client device in real time as the user utilizes the client device to access and navigate the software application(s) to display these recommendations.

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