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RELEVANCE RANKING OF PRODUCTIVITY FEATURES FOR DETERMINED CONTEXT

机译:相关性上下文的生产力特征的相关性排序

摘要

The present disclosure relates to processing operations configured to identify and present productivity features that are contextually relevant for user access to an electronic document. In doing so, signal data is evaluated to determine a context associated with user access to an electronic document and insights, from the determined context, are utilized to rank productivity features for relevance to a user workflow. As an example, an intelligent learning model is trained and implemented to identify what productivity features are most relevant to a current task of a user. Productivity features are identified and ranked for contextual relevance. A notification comprising one or more ranked productivity features is presented to a user. In one example, the notification is presented through a user interface of an application/service. For instance, a user interface pane is surfaced to present suggestions. However, in alternative examples, notification of ranked productivity features is presented through different modalities.
机译:本公开涉及处理操作,该处理操作被配置为识别和呈现与用户访问电子文档的上下文相关的生产率特征。在这样做时,评估信号数据以确定与用户对电子文档的上下文以及从所确定的上下文中的洞察中的洞察,用于对用户工作流程的相关性进行排序。作为示例,训练和实现智能学习模型以确定与用户的当前任务最相关的生产率特征。识别生产力特征,并排名为上下文相关性。包括一个或多个排名的生产率特征的通知呈现给用户。在一个示例中,通过应用程序/服务的用户界面呈现通知。例如,用户界面窗格符合提出建议。然而,在替代示例中,通过不同的方式呈现排名的生产率特征的通知。

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