Abstract: Methods and systems are disclosed for scheduling a task of a user based on a cyber-physical-social (CPS) context of activities. The present disclosure is directed to increasing the efficiency of performing tasks by grouping tasks with the same or similar task CPS contexts so that they are performed in conjunction with one another. A stream of user activities is received that encompasses the CPS context, tasks are identified and classified based on a CPS context model. The CPS model is trained using CPS context and annotations for identified tasks as input to create classes of tasks. The classes of tasks from the model are used to group similar tasks. The present disclosure enables users to receive recommendations on clustering tasks with the same or similar contexts based on an online tool, a location, and collaborators to be performed together to improve productivity.

Abstract: The present disclosure relates to systems and methods for an interactive, intelligent hub built around the completion of a task. This hub brings together resources, information, suggested steps, and other automated assistance to facilitate the completion of the task. AI-based assistance may indicate which steps can be completed by automated processes, and dispatch those processes, or suggest resources to assist in the completion of other steps. The hub displays the current status of the task, and lives until the completion of the task, or abandonment by the user.

Abstract: The present disclosure relates to systems and methods for an interactive, intelligent hub built around the completion of a task. This hub brings together resources, information, suggested steps, and other automated assistance to facilitate the completion of the task. AI-based assistance may indicate which steps can be completed by automated processes, and dispatch those processes, or suggest resources to assist in the completion of other steps. The hub displays the current status of the task, and lives until the completion of the task, or abandonment by the user.

Abstract: The present disclosure relates to systems and methods for an interactive, intelligent hub built around the completion of a task. This hub brings together resources, information, suggested steps, and other automated assistance to facilitate the completion of the task. AI-based assistance may indicate which steps can be completed by automated processes, and dispatch those processes, or suggest resources to assist in the completion of other steps. The hub displays the current status of the task, and lives until the completion of the task, or abandonment by the user.

Abstract: An enhanced task management feature can provide enhanced task management capabilities including making the entering of new tasks in an electronic application easier for the user, such as having the user see suggestions of where to put the new task and, in some cases, providing suggestions for details associated with the task. The enhanced task management feature can receive task input associated with a task item from an application; use the task input and at least a user-specific model to identify at least one likely task list name for the task item; and provide a suggested task list name from the at least one likely task list name to the application for display. The enhanced task management feature can receive from user input a task list name and the task item and the task item can then be assigned to a task list associated with the task list name.

Abstract: Methods and systems are disclosed for scheduling a task of a user based on a cyber-physical-social (CPS) context of activities. The present disclosure is directed to increasing the efficiency of performing tasks by grouping tasks with the same or similar task CPS contexts so that they are performed in conjunction with one another. A stream of user activities is received that encompasses the CPS context, tasks are identified and classified based on a CPS context model. The CPS model is trained using CPS context and annotations for identified tasks as input to create classes of tasks. The classes of tasks from the model are used to group similar tasks. The present disclosure enables users to receive recommendations on clustering tasks with the same or similar contexts based on an online tool, a location, and collaborators to be performed together to improve productivity.

Abstract: Aspects of the present disclosure relate to a smart coach for optimizing an ordering of tasks. In examples, a plurality of tasks associated may be received by the smart coach. In some instances, the plurality of tasks may be for one or more users. Task related information associated with at least one optimization criterion may be received at a user interface or retrieved from storage. An ordering of the plurality of tasks with respect to the at least one optimization criterion may then be generated, where the at least one optimization criterion may be based on at least one of a user optimization goal, an efficiency goal, and a task priority level. The optimized ordering of tasks may then be displayed at a user interface in a task execution order. In some examples, the ordering of tasks may be displayed as an agenda and/or in a calendar view.

Abstract: An enhanced task management feature can provide enhanced task management capabilities including making the entering of new tasks in an electronic application easier for the user, such as having the user see suggestions of where to put the new task and, in some cases, providing suggestions for details associated with the task. The enhanced task management feature can receive task input associated with a task item from an application; use the task input and at least a user-specific model to identify at least one likely task list name for the task item; and provide a suggested task list name from the at least one likely task list name to the application for display. The enhanced task management feature can receive from user input a task list name and the task item and the task item can then be assigned to a task list associated with the task list name.