Abstract: Systems and methods are disclosed for meeting completion. In one implementation, a message generated in relation to a meeting is received. The message is processed to identify a first action item and a first user associated with the first action item. The first action item is assigned to the first user. Performance of the first action item by the first user is tracked. The performance of the first action item by the first user is presented within an action tracking interface.

Abstract: When content is shared, the sharer of the content is identified, as are the audience members. An entry is generated in a data store that identifies the content, the sharer and the audience members. Content retrieval requests can then be processed against the data store to identify and return content.

Abstract: Automatically extracting and completing tasks associated with a communication is provided. In some examples, an application, such as a task management application, may generate nodes based on properties extracted from a communication, generate tasks based on the nodes, and construct a graph based on the nodes and the tasks. The task management application may also perform a prioritization of the tasks within the graph based on the properties of the nodes, order the tasks within the graph based on the prioritization of the tasks, and provide a task management interface to present the tasks within the graph. The task management application may also transmit the tasks within the graph to a task extraction engine of the task management application in response to a modification input executed on the graph.

Abstract: Systems and methods are disclosed for meeting completion. In one implementation, a message generated in relation to a meeting is received. The message is processed to identify a first action item and a first user associated with the first action item. The first action item is assigned to the first user. Performance of the first action item by the first user is tracked. The performance of the first action item by the first user is presented within an action tracking interface.

Abstract: Enhanced relationship graph signals are provided. A productivity service initiates operations to provide enhanced relationship graph signals by retrieving relationship attribute(s) between two users of a productivity service. Interactivity attribute(s) between the two users of the product service are also retrieved. An enhanced signal is generated based on the relationship and interactivity attributes. The enhanced signal is stored within a relationship graph.

Abstract: A communication ranking scheme is provided based on a relationship graph. A communication service initiates operations to provide the communication ranking scheme by identifying an attribute of a communication upon receiving the communication intended for a recipient. A relationship graph is queried to retrieve a signal and a signal value associated with the attribute. The signal value is processed with a weight value to generate a weighted signal value that is used to compute a rank value for the communication. The rank value is provided along with the communication to a client application for ordering the communication based on the rank value.

Abstract: Automatically extracting and completing tasks associated with a communication is provided. In some examples, an application, such as a task management application, may generate nodes based on properties extracted from a communication, generate tasks based on the nodes, and construct a graph based on the nodes and the tasks. The task management application may also perform a prioritization of the tasks within the graph based on the properties of the nodes, order the tasks within the graph based on the prioritization of the tasks, and provide a task management interface to present the tasks within the graph. The task management application may also transmit the tasks within the graph to a task extraction engine of the task management application in response to a modification input executed on the graph.

Abstract: Automatic identification of experts and areas of expertise in an organization is provided. An analysis processing engine retrieves data from various data repositories, preprocesses the data, and employs algorithms for recognition of words and phrases from which a top number of phrases are selected as areas of expertise. The analysis processing engine stores the selected areas of expertise in a graph structure. Once one or more areas of expertise are identified and stored in the graph structure, the analysis processing engine queries the graph structure for identification and ranking of experts on the one or more areas of expertise. Bidirectional graph edges are added between the areas of expertise nodes and the corresponding experts of the areas of expertise such that both targeted and exploratory queries are enabled.

Abstract: When content is shared, the sharer of the content is identified, as are the audience members. An entry is generated in a data store that identifies the content, the sharer and the audience members. Content retrieval requests can then be processed against the data store to identify and return content.