Microsoft Technology Licensing, LLC

Jason T Creighton

Ajoy Nandi

Eric J Horvitz

John Charles Krumm

Ryen William White

Nikrouz Ghotbi

Paul B Koch

Melissa Nicole Lim

Marius Cristian Constantin

Jeffrey J Wall

Jeremy Littel

Somanath Krishnaswamy

Mangesh Deshpande

Kent C Mai

Ping Zhang

Joyce Kuo

Vallabh Patade

Ian S Petersen

Amol Wankhede

Marius C Constantin

A computer-implemented technique is described herein for facilitating a user's repeated execution of the same computer-implemented actions. The technique performs this task by determining patterns in the manner in which the user repeats requests associated with certain computer-implemented actions. For example, the technique determines context-dependent patterns in the manner in which the user submits search requests to a search system. The technique then leverages those patterns by proactively providing a request-assistance tool to the user in those context-specific circumstances in which the user is likely to perform the repetitive computer-implemented actions. The digital action-assistance tool provides various kinds of assistance to the user in performing the repetitive computer-implemented actions.

Context-dependent digital action-assistance tool

Task assignments are identified. A dataset that includes one or more electronic messages is received. Then, one or more pending tasks in the dataset are identified, and each of a plurality of people who are mentioned in the dataset is also identified. Then, for each of the pending tasks, one or more of the identified people are identified as potentially being people who are assigned to complete the pending task, and the pending task is associated with these identified one or more of the identified people. For each of the pending tasks, one or more of the identified people are also identified as potentially being people for whom the pending task is to be completed, and the pending task is also associated with these identified one or more of the identified people.

Identifying task assignments

Systems and methods for controlling an intentional crash of a software application. One system includes a computing device including an electronic processor. The electronic processor is configured to receive a crash setting for the software application from a configuration server. The crash setting has a first value or a second value. The electronic processor is also configured to detect an unexpected use of the software application during execution. The electronic processor is configured to, in response to detecting the unexpected use and the crash setting having the first value, intentionally crash the software application causing a generation of a crash report describing a state of the software application when the unexpected use occurred. The electronic processor is configured to, in response detecting the unexpected use and the crash setting having the second value, not intentionally crash the software application.

Conditionally crashing software applications to track software use

Calendar and scheduling applications organize and display user events and provide event reminders. A method of triggering a reminder includes accessing a reminder which describes an event. An individual associated with the event, other than the user, is identified. A future time is predicted when the user will be within proximity of the individual. A time to trigger the reminder for presentation to the user is determined, such that the time to trigger the reminder occurs in advance of the predicted future time when the user will be within proximity of the individual. Based on a determination that the time for triggering the reminder has occurred, the reminder is triggered to be presented to the user.

Intelligent surfacing of reminders

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Bellevue, WA, United States of America

Jason T Creighton