Microsoft Technology Licensing, LLC

Other

Russell Allen Herring, Jr

Ryen William White

Adam Fourney

Robert Alexander Sim

Paul Nathan Bennett

Elnaz Nouri

Nirupama Chandrasekaran

Vanessa Graham Murdock

Mohammed Fadel Shatnawi

Andrey Tolskyakov

Justin Jiajun Hua

The present disclosure provides systems and methods for user interaction and task completion using multiple devices. A set of devices may be used to perform a task, such that different devices may perform different steps of the task. A device management service may update state information at each device of the set, thereby enabling a user to interact with any of the computing devices to perform the task. A device management service may also automatically determine which device should be used by the user, based on task or step requirements, device characteristics, and device capabilities, among other examples. Thus, rather than being required to continue a task on the same device (even when the device is not well-suited for the current step or task), the user is provided with the option to use and, in some instances, is automatically transitioned to use, different devices within the set.

User interaction and task management using multiple devices

Systems and methods can be implemented to provide suggestions to a user device to execute user tasks in a variety of applications. In various embodiments, a set of tasks of a user from a number of task sources are identified for possible consolidation. The tasks in the set can be analyzed to identify a location to accomplish the tasks, estimate times to complete the tasks at the identified locations, and compute routes to the locations from a starting location or compute routes with respect to a route to another location of another task of the set of tasks. The identified locations, the estimated times, and the computed routes can be used to determine which tasks of the set of tasks are available for consolidation. One or more suggestions of task consolidations can be generated to or within the user device. Additional systems and methods are disclosed.

Location-based task suggestions

A digital task document can include instructions for performing a task, and a task state data structure can indicate a state of completion of the task. A first update of the data structure can be performed in response to visual user input received from a user profile via a first computer application/device. A second update of the data structure can be performed in response to natural language input received from the user profile via the second computer application/device. A first set of task guidance can be provided to the user profile via the first application/device in a visual format by displaying the task document on a computer display. A second set of task guidance can be provided to the user profile via the second application/device in a natural language format. The first and second sets of task guidance can be provided using the task document and the data structure.

Computerized task guidance across devices and applications

A proximity of a first computing device with a second computing device can be detected. In response to the detecting of the proximity, it can be determined that a computer-readable qualification for a type of proactive engagement is met using the detected proximity and possibly a non-proximity state of the first device. The type of proactive engagement can be matched in the computer system with an operation that is programmed to be performed using a computerized natural language digital assistant. In response to the determining that the qualification for the type of proactive engagement is met, the technique can include performing a user engagement action via the second device. The user engagement action can be of a type indicated by the type of proactive engagement. The user engagement action can facilitate a computerized communication session between a computer-readable user profile and the computerized natural language digital assistant.

Proximity-based engagement with digital assistants

Object model based mapping may be provided. First, backend data may be received defining data constructs in a backend system. Then entity data may be received defining data constructs in an entity model. User selectable elements may then be received defining a process associating the backend data with the entity data. Next, code may be produced, based on the received user selectable elements, configured to implement the process.

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Sammamish, WA, United States of America

Russell Allen Herring, Jr