Microsoft Technology Licensing, LLC

Bichong Li

Wendy Guo

Leanna Holly Robb

Nagendra Kalyan Nanduru

Feng Zhang

Sandeep Seri

Siqi Yang

Tor Andrew Imsland

Qi Zhang

Vivek Chauhan

Noelle Renee Beaujon

Jinkai Zhang

Vineet Batta

Michelle Casanova

A computer implemented method includes receiving a start date and an end date specifying a future absence or away-from-work time period for a user, generating an away from office communication specifying the away-from-work time period, retrieving via the computer a list of collaborators based on frequency and duration of recent interactions with the user, receiving via the computer a selection of collaborators from the list, identifying meetings involving the user during the away-from-work time period, generating via the computer a list of user viewable items for the user to complete prior to the away-from-work time period, and generating via the computer a list of items for the user to attend to upon return from the away-from-work time period for presentation to the user upon return.

Integrated time away management mechanism

In non-limiting examples of the present disclosure, systems, methods and devices for surfacing email suggestions are presented. A first user account associated with a composer of an email may be identified. Core working hour and a time zone associated with that first user account may be determined. One or more recipient user accounts included in the email may be identified. Core working hours and a time zone associated with the recipient user accounts may be identified. If more than a threshold number, percentage, and/or ratio of the recipient users is not currently in core working hours when the email is being drafted/sent, a suggestion may be surfaced in association with the email to send the email at a later time when more recipient users are in their core working hours.

Suggested delay delivery of electronic messages

A system and method for computing a metric indicating a user operation of an application is described. The system accesses online activity data of a user operation of the application. The system filters the online activity data based on a preset time range. An after-hours activity score is calculated based on a type of activity or a duration of an activity from the filtered online activity data, and a weight assigned to the type of activity or the duration of the activity. The system computes an after-hours metric based on the after-hours activity score. A configuration setting for the application based on the after-hours metric is applied to the application.

Computation of after-hours activities metrics

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Suzhou, China

Bichong Li