Relevance ranking of productivity features for determined context
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.
Microsoft Technology Licensing, LLC
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Yu Been Shikha Devesh Penelope Ann Anav Gwenyth Alanna Vabalis Patricia Hendricks Alyssa Rachel Susan Michele
Lee Desai Collisson Silverman Hardiman Balik Mayo Hendrich