Abstract: Systems and methods for inferring relationships between a target person and another entity according to accessed or captured communication content of the target person are presented. Various communications (communication content) of a target person are accessed or captured. Communication content is analyzed to identify key terms and/or key phrases of the captured communication content. Based, at least, on the identified key terms and key phrases, one or more relationships between the target person and another entity are inferred. A relationship record of the target person is updated with information regarding the inferred relationship.

Abstract: Disclosed in some examples are methods, systems, machine-readable media, and devices which provide for real-time personalized suggestions for participants in a network-based communication service. The personalized suggestions may include options for taking actions, content suggestions, and smart replies. These suggestions may be based upon the current conversation and are delivered personally to each participant.

Abstract: Reminders are provided to a user. A particular reminder for the user and a confidence level associated with the particular reminder are input. A current priority level for the particular reminder is then computed, where this computation is based on reminder prioritization factors that include this confidence level, a current context for the user, and additional information about this current context. One or more user notification methods for providing the particular reminder to the user are then selected, where this selection is based on notification method selection factors that include the computed current priority level for the particular reminder, the current context for the user, and the additional information about this current context. The selected user notification methods are then utilized to provide the particular reminder to the user.

Abstract: Task information is exposed to providers of online services. A dataset that includes one or more electronic messages is received. Then, one or more task intents in the dataset are identified, where each of the identified task intents is a specific task that is to be completed. Then, for each of the identified task intents, one or more service providers each of whom offers one or more online services that are capable of assisting in the fulfillment of the identified task intent are identified, and information associated with the identified task intent is exposed to each of the identified service providers.

Abstract: 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.

Abstract: Techniques are described herein that are capable of performing intent-based scheduling via a digital personal assistant. For instance, an intent of user(s) to perform an action (a.k.a. activity) may be used to schedule time (e.g., on a calendar of at least one of the user(s)) in which the action is to be performed. Examples of performing an action include but are not limited to having a meeting, working on a project, participating in a social event, exercising, and reading.

Abstract: Techniques are described herein that are capable of performing intent-based scheduling via a digital personal assistant. For instance, an intent of user(s) to perform an action (a.k.a. activity) may be used to schedule time (e.g., on a calendar of at least one of the user(s)) in which the action is to be performed. Examples of performing an action include but are not limited to having a meeting, working on a project, participating in a social event, exercising, and reading.

Abstract: Commanding and task completion through self-messages is described. In implementations, message actions may be automatically initiated and performed using self-messages that a user sends to the user's own accounts. In order to do so, a message analytics module operates to check messages associated with a user account and recognize self-messages addressed by the user to the user. The message analytics module further analyzes recognized self-messages to derive the intent of the user in sending the message. Different classifications may be associated with different message actions performable via the message analytics module and/or a digital assistant invoked by the message analytics module. Thus, based on the classification of a self-message into one or more particular categories, corresponding message actions that are specified for the particular categories are preformed to handle and manage the self-messages. In this manner, a user is able command a digital assistant and otherwise specify different tasks.

Abstract: Systems, methods and computer program products are described herein that automatically identify a task to be performed by a user, obtain an estimate of an amount of time required to complete the task, identify a period of user availability, determine that the period of user availability is suitable for performing at least a portion of the task, and in response to such a determination, cause a reminder or notification about the task to be presented to the user. The determination that the period of user availability is suitable for performing at least a portion of the task may be based at least in part on the estimate of the amount of time required to complete the task. A task completion time model may be automatically generated for the user and utilized to obtain the estimate of the amount of time required to complete the task.

Abstract: Aspects of the technology described herein provide a more efficient user interface by providing suggestions that are tailored to a specific user's interests. The suggestions may be provided by a personal assistant or some other application running on a user's computing device. A goal of the technology described herein is to provide relevant suggestions when the user can and actually wants to use them. The suggestions are designed to provide information or services the user wants to use.

Abstract: A system that analyses content of electronic communications may automatically extract requests or commitments from the electronic communications. In one example process, a processing component may analyze the content to determine one or more meanings of the content; query content of one or more data sources that is related to the electronic communications; and based, at least in part, on (i) the one or more meanings of the content and (ii) the content of the one or more data sources, automatically identify and extract a request or commitment from the content. Multiple actions may follow from initial recognition and extraction, including confirmation and refinement of the description of the request or commitment, and actions that assist one or more of the senders, recipients, or others to track and address the request or commitment, including the creation of additional messages, reminders, appointments, or to-do lists.

Abstract: A system that analyses content of electronic communications may automatically detect requests or commitments from the electronic communications. In one example process, a processor may identify a request or a commitment in the content of the electronic message; based, at least in part, on the request or the commitment, determine an informal contract; and execute one or more actions to manage the informal contract, the one or more actions based, at least in part, on the request or the commitment.