Abstract: Various embodiments are directed to automatically determining when meetings are related to each other. The relationship between meetings may be stored in a meeting-oriented knowledge graph that can be analyzed to provide meeting analytics. Various technologies can leverage the meeting relationship information to provide improved meeting services to users. For example, meeting suggestions may be presented to a user with suggested meeting parameters (e.g., suggested attendees, suggested location, suggested topic) that are accurate because a relationship between meetings is used to predict the parameters. The information in the meeting-oriented knowledge graph can be used to generate various analytics and visualizations that help users plan or prepare for meetings.

Abstract: A system and method for allocating a recurring resource is described. The system receives a request to allocate the recurring resource of an application to computing devices associated with one or more users. The system identifies a cadence of the recurring resource and a range based on the cadence. A period is determines based on the cadence and the range. The system accesses user resource data of the application for each period and iteratively computes a resource availability score for the period based on the corresponding user resource data. The system determines that the resource availability score of an instance of the period is less than a threshold value and allocates the recurring resource to instances of the period where the corresponding resource availability score exceeds the threshold value.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for assigning conference rooms are presented. A meeting request may be received by an electronic meeting service. Meeting fit scores may be calculated for the meeting request and one or more conference rooms. The meeting fit scores may be based on location, capacity, and/or audio-visual capabilities. The meeting request may be assigned to a conference room with a highest meeting fit score. A meeting request may be re-assigned to a different conference room based on a conference room becoming available that has a higher meeting fit score. A meeting request may be re-assigned to a different conference room based on characteristics of the meeting request being modified (e.g., fewer invitees, more invitees, different location specified), and thus, the meeting fit scores for conference rooms changing based on those modifications.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for prioritizing calendar events with artificial intelligence are presented. A request to schedule a new calendar event for a specified period may be received. A conflicting calendar event during the specified time period may be identified. An event priority score for the new calendar event may be compared with an event priority score for the conflicting calendar event, wherein the event priority scores are generated via application of a statistical machine learning model to a plurality of factors associated with the new calendar event and the conflicting calendar event. A selectable option to replace the conflicting calendar event with the new calendar event may be presented if the event priority score for the new calendar event is higher than the event priority score for the conflicting calendar event.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for assigning conference rooms are presented. A meeting request may be received by an electronic meeting service. Meeting fit scores may be calculated for the meeting request and one or more conference rooms. The meeting fit scores may be based on location, capacity, and/or audio-visual capabilities. The meeting request may be assigned to a conference room with a highest meeting fit score. A meeting request may be re-assigned to a different conference room based on a conference room becoming available that has a higher meeting fit score. A meeting request may be re-assigned to a different conference room based on characteristics of the meeting request being modified (e.g., fewer invitees, more invitees, different location specified), and thus, the meeting fit scores for conference rooms changing based on those modifications.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for routing meeting requests by a digital assistant service are presented. A request to schedule a meeting between an invitee and a principal may be received by a digital assistant service, wherein the request is sent by an agent of the principal. The digital assistant service may determine that the agent is a delegate of the principal with scheduling authority. The digital assistant service may further determine that follow-up information for the meeting is required, and the digital assistant service may route an electronic message requesting the follow-up information directly the agent-delegate. Other aspects describe mechanisms for routing meeting requests from third parties directly to delegates, rather than sending those communications directly to principals.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for matching user tone to digital assistant response types and tones while assisting with meeting scheduling are presented. An electronic message may be received by a digital assistant service. The digital assistant service may detect an intent to schedule a meeting and identify an urgency level associated with the message. The digital assistant may respond to the scheduling user with a message having a tone corresponding to the identified urgency level. The digital assistant may also perform a follow-up action for scheduling the meeting in a manner consistent with the urgency level of the scheduling user. For example, the digital assistant may attempt to schedule the meeting in a higher priority manner if there is a high urgency associated with the message, and a lower priority manner if there is a low urgency associated with the message.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for prioritizing calendar events with artificial intelligence are presented. A request to schedule a new calendar event for a specified period may be received. A conflicting calendar event during the specified time period may be identified. An event priority score for the new calendar event may be compared with an event priority score for the conflicting calendar event, wherein the event priority scores are generated via application of a statistical machine learning model to a plurality of factors associated with the new calendar event and the conflicting calendar event. A selectable option to replace the conflicting calendar event with the new calendar event may be presented if the event priority score for the new calendar event is higher than the event priority score for the conflicting calendar event.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for matching user tone to digital assistant response types and tones while assisting with meeting scheduling are presented. An electronic message may be received by a digital assistant service. The digital assistant service may detect an intent to schedule a meeting and identify an urgency level associated with the message. The digital assistant may respond to the scheduling user with a message having a tone corresponding to the identified urgency level. The digital assistant may also perform a follow-up action for scheduling the meeting in a manner consistent with the urgency level of the scheduling user. For example, the digital assistant may attempt to schedule the meeting in a higher priority manner if there is a high urgency associated with the message, and a lower priority manner if there is a low urgency associated with the message.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for assisting with related calendar events are presented. One or more signals associated with a plurality of calendar events may be analyzed. A determination may be made as to whether, based on the analysis, the plurality of calendar events are related. The plurality of calendar events may be linked into a searchable entity with grouped properties. A search that indicates at least one of the grouped properties may be received, and information associated with the searchable entity may be caused to be displayed. In some examples, a digital assistant may automatically schedule a next event in a linked chain of events. In additional examples, an event scheduling service may utilize data from linked events to generate event metrics associated with task completion.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for indicating time-cost allocation for an organization for a specified time period are presented. A virtual time coin system may be utilized to track temporal transactions made by organizational entities (e.g., organizational groups, organizational employees). A time coin application may track temporal transactions (e.g., meeting invites, meeting cancelations, meeting expansions) made by organizational entities, and those transactions may be stored on blocks of a temporal blockchain that is duplicated across a plurality of nodes in a distributed ledger. Each temporal transaction may be associated with a withdrawal or deposit of time coins from a time coin repository corresponding to the organizational entity or entities that were party to a transaction. The time coin application may analyze bocks in temporal blockchains and cause the results of that analysis to be graphically displayed.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for routing meeting requests by a digital assistant service are presented. A request to schedule a meeting between an invitee and a principal may be received by a digital assistant service, wherein the request is sent by an agent of the principal. The digital assistant service may determine that the agent is a delegate of the principal with scheduling authority. The digital assistant service may further determine that follow-up information for the meeting is required, and the digital assistant service may route an electronic message requesting the follow-up information directly the agent-delegate. Other aspects describe mechanisms for routing meeting requests from third parties directly to delegates, rather than sending those communications directly to principals.