METHODS AND SYSTEM FOR MANAGING PREDICTIVE MODELS

    公开(公告)号:US20150347908A1

    公开(公告)日:2015-12-03

    申请号:US14500990

    申请日:2014-09-29

    Applicant: Apple Inc.

    CPC classification number: G06N5/04 G06N5/043 G06N20/00 H04L67/10

    Abstract: Disclosed herein is a technique for implementing a framework that enables application developers to enhance their applications with dynamic adjustment capabilities. Specifically, the framework, when utilized by an application on a mobile computing device that implements the framework, can enable the application to establish predictive models that can be used to identify meaningful behavioral patterns of an individual who uses the application. In turn, the predictive models can be used to preempt the individual's actions and provide an enhanced overall user experience. The framework is configured to interface with other software entities on the mobile computing device that conduct various analyses to identify appropriate times for the application to manage and update its predictive models. Such appropriate times can include, for example, identified periods of time where the individual is not operating the mobile computing device, as well as recognized conditions where power consumption is not a concern.

    METHODS AND SYSTEM FOR MANAGING PREDICTIVE MODELS

    公开(公告)号:US20200034725A1

    公开(公告)日:2020-01-30

    申请号:US16538706

    申请日:2019-08-12

    Applicant: Apple Inc.

    Abstract: Disclosed herein is a technique for implementing a framework that enables application developers to enhance their applications with dynamic adjustment capabilities. Specifically, the framework, when utilized by an application on a mobile computing device that implements the framework, can enable the application to establish predictive models that can be used to identify meaningful behavioral patterns of an individual who uses the application. In turn, the predictive models can be used to preempt the individual's actions and provide an enhanced overall user experience. The framework is configured to interface with other software entities on the mobile computing device that conduct various analyses to identify appropriate times for the application to manage and update its predictive models. Such appropriate times can include, for example, identified periods of time where the individual is not operating the mobile computing device, as well as recognized conditions where power consumption is not a concern.

    METHODS AND SYSTEM FOR MANAGING PREDICTIVE MODELS
    3.
    发明申请
    METHODS AND SYSTEM FOR MANAGING PREDICTIVE MODELS 审中-公开
    用于管理预测模型的方法和系统

    公开(公告)号:US20150347907A1

    公开(公告)日:2015-12-03

    申请号:US14500985

    申请日:2014-09-29

    Applicant: Apple Inc.

    CPC classification number: G06N5/04 G06N5/043 G06N20/00

    Abstract: Disclosed herein is a technique for implementing a framework that enables application developers to enhance their applications with dynamic adjustment capabilities. Specifically, the framework, when utilized by an application on a mobile computing device that implements the framework, can enable the application to establish predictive models that can be used to identify meaningful behavioral patterns of an individual who uses the application. In turn, the predictive models can be used to preempt the individual's actions and provide an enhanced overall user experience. The framework is configured to interface with other software entities on the mobile computing device that conduct various analyses to identify appropriate times for the application to manage and update its predictive models. Such appropriate times can include, for example, identified periods of time where the individual is not operating the mobile computing device, as well as recognized conditions where power consumption is not a concern.

    Abstract translation: 这里公开了一种用于实现框架的技术,其使应用开发者能够通过动态调整功能来增强其应用。 具体地说,该框架当被实施框架的移动计算设备上的应用程序使用时,可以使应用程序能够建立可用于识别使用该应用程序的个人的有意义的行为模式的预测模型。 反过来,预测模型可以用于抢占个人的行为并提供增强的整体用户体验。 该框架被配置为与移动计算设备上的其他软件实体进行接口,进行各种分析以确定应用程序管理和更新其预测模型的适当时间。 这种适当的时间可以包括例如个体不操作移动计算设备的识别的时间段以及功率消耗不是关注的公认条件。

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