Microsoft Technology Licensing, LLC

Orkhan Muradov

Patrick Michael Gan

Sugandha SudeshKumar Kapoor

Brian Daniel Meersma

Nikhil Vilas Kulkarni

Vivek Mogalapalli

Adri Verlaan

Uladzislau Sudzilouski

Theo Lorrain-Hale

Simoune Rebekah Morena Valerio Lucas

Cosmin Catrinescu

Maria Montserrat Lozano Dieck

Xiaojun Li

Hansel Ivan Gene Ip

Yi Ke

Andrew Boktor

Michal Bloch Ron

Vishwak Reddy Neravetla

Kori Michelle Loomis

Carl Frederick Hirschman

Hang Vi Quan

Non-limiting examples of the present disclosure pertain to management over the type of notification that is generated and presented to a user relative to an occurrence of a message notification. Processing is executed that evaluates a relevance of a content update to content that is already presented to a user through host application/service endpoints. This helps determine how to present a graphical user interface (GUI) notification as well as link that GUI notification to existing communications that are identified as contextually relevant. Trained artificial intelligence modeling is applied that executes relevance analysis to aid generation of a GUI notification. Said relevance analysis correlates a content portion, of a content update, with a content sub-range assigned in a live representation of the distributed collaborative canvas, where a live representation is an editable and synchronized representation of the distributed collaborative canvas that presents the content sub-range inline within a host application/service endpoint.

Automated notification of content update providing live representation of content inline through host service endpoint(s)

The present disclosure is directed to automated notification generation, where a generated notification comprises a live representation of a content update that is linked and synchronized with a distributed collaborative canvas (or other source content) comprising the content portion which is being updated. A non-limiting example of a content update is a message notification, such as an at-mention (@mention), that is included inline within a content portion. Other triggers for automated notification generation are also described. Generation of an exemplary notification comprises a contextual relevance analysis that not only selects, for a recipient of the message notification, a specific host application/service endpoint to present the notification in but also determines how/what specific content to present inline within the selected host application/service endpoint. The notification is automatically generated and provided to a selected host application/service endpoint for rendering of the notification inline with content of the host application/service endpoint.

A system prevents user-activity events from triggering transmission of duplicative notifications to multiple applications. The system may receive subscriptions for notifications from multiple applications installed on a single client device. Trigger criteria for the applications' subscriptions overlap such that a 'single' user-activity event may satisfy trigger criteria for multiple subscriptions. The system receives event data that indicates when a user-activity event has satisfied trigger criteria for the multiple subscriptions associated with the client device. Rather than indiscriminately transmitting duplicative notifications, the system selects individual 'satisfied' subscriptions to fulfill. Thus, when subscriptions are satisfied for multiple different applications on a single client device, the system may deploy a subscription prioritization engine to select a single one of the multiple different applications to transmit a notification to. Stated alternatively, for individual user-activity events, the subscription prioritization engine determines a subset of &#x201c;satisfied&#x201d; subscriptions to fulfill and to refrain from fulfilling.

Preventing transmission of duplicate notifications to multiple applications on a client device

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Kirkland, WA, United States of America

Orkhan Muradov