Microsoft Technology Licensing, LLC

Nagendra Kalyan Nanduru

Wendy Guo

Leanna Holly Robb

Bichong Li

Feng Zhang

Sandeep Seri

Tor Andrew Imsland

Siqi Yang

Qi Zhang

Umashree Narayanaswamy

Yaming Liu

Vineet Batta

Vivek Chauhan

Koushik Dasgupta

Noelle Renee Beaujon

Mathew Kuzhithattil Aniyan

Jinkai Zhang

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

Instant message servers configured for automatic instant message usage control in an instant message system are disclosed herein. In one example, an instant message server can be configured to determine an IM usage time of the user during the one or more IM sessions based on numbers of the detected occurrences of the IM events and weight factors corresponding to each type of the IM events. The weight factors correlate the numbers of occurrences of each type of the IM events to a corresponding IM usage period for each occurrence. The instant message server can then perform a comparison of the determined IM usage time of the user with a preset threshold and when the IM usage time of the user exceeds the threshold based on the comparison, automatically adjust the IM service provided to the user by the instant message server.

Automatic usage control of instant messages in computing systems

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Redmond, WA, United States of America

Nagendra Kalyan Nanduru