Abstract: A candidate virtual team is generated using a team prediction model. The team prediction model is trained based on user feedback. Activity data of a user is collected, the activity data is associated with activities in which the user and a set of other users have engaged. A candidate virtual team associated with the collected activity data is generated using a team prediction model and the candidate virtual team is presented to the user using an interface. User feedback data associated with the generated candidate virtual team is received from the user. The team prediction model is trained using the received user feedback data, whereby accuracy of future generated candidate virtual teams generated by the team prediction model is improved during the training. The training of the team prediction model based on user feedback improves the generation of virtual teams over time.

Abstract: Technology is disclosed for controlling the processing and presentation of group data on computing devices to provide improved computing applications, electronic communications, and user computing experiences. Data indicating a group of people may be programmatically determined or inferred, such as from the user activity of a particular user. Group data characterizing the group of people may be generated and contextualized or personalized for the user based on a user context or intent. Aspects of the contextualized group data may be provided to the user in response to an interaction with an indication of the group or group member. The group data may be provided as a set of group information items, and further may be formatted or assembled for presentation based on the user context, and/or may be consumed by a computing application or service to provide an improved user computing experience.

Abstract: A network map of an individual's implicit and explicit people relationships across multiple workloads is provided. Relationships between people may be leveraged and ranking for people relationships may be performed based on activities across multiple workloads. People relationships may be displayed in the network map to provide a visual understanding of relationships and connections. Navigation to any person represented in the network map may be enabled, and commonalities in relationships between a navigating user and a given person navigated to in the network map may be exposed. Trending items and activity streams for a person or group of persons may be shown in the network map.

Abstract: A network map of an individual's implicit and explicit people relationships across multiple workloads is provided. Relationships between people may be leveraged and ranking for people relationships may be performed based on activities across multiple workloads. People relationships may be displayed in the network map to provide a visual understanding of relationships and connections. Navigation to any person represented in the network map may be enabled, and commonalities in relationships between a navigating user and a given person navigated to in the network map may be exposed. Trending items and activity streams for a person or group of persons may be shown in the network map.

Abstract: A network map of an individual's implicit and explicit people relationships across multiple workloads is provided. Relationships between people may be leveraged and ranking for people relationships may be performed based on activities across multiple workloads. People relationships may be displayed in the network map to provide a visual understanding of relationships and connections. Navigation to any person represented in the network map may be enabled, and commonalities in relationships between a navigating user and a given person navigated to in the network map may be exposed. Trending items and activity streams for a person or group of persons may be shown in the network map.

Abstract: An activity stream for an individual or group of individuals across multiple workloads comprising activity data may be provided. Activity data may include various types of data/information received from a variety of information sources. Received activity data may be stored, and an activity stream for an individual or group of individuals may be generated. A timeline view may be generated for each activity stream. Upon request, the timeline view for a given individual or group of individuals (grouped according to any desired grouping) may be presented in a user interface to allow a requesting user to view activity data/information for the given individual or group of individuals.

Abstract: A network map of an individual's implicit and explicit people relationships across multiple workloads is provided. Relationships between people may be leveraged and ranking for people relationships may be performed based on activities across multiple workloads. People relationships may be displayed in the network map to provide a visual understanding of relationships and connections. Navigation to any person represented in the network map may be enabled, and commonalities in relationships between a navigating user and a given person navigated to in the network map may be exposed. Trending items and activity streams for a person or group of persons may be shown in the network map.