Abstract: A software agent, that is used to assist in providing a service, receives communications from a set of users that are attempting to use the software agent. The communications include communications that are interacting with the software agent, and communications that are not interacting with the software agent. The software agent performs natural language processing on all communications to identify such things as user sentiment, user concerns or other items in the content of the messages, and also to identify actions taken by the users in order to obtain a measure of user satisfaction with the software agent. One or more action signals are then generated based upon the identified user satisfaction with the software agent.

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: Linguistic analysis based correlation of distinct events is provided. In examples, trouble shooting tickets may be received over a time period. A linguistic analysis may be performed on one or more portions of the one or more comments using a linguistic model and a similarity score may be computed for one or more keywords within the one or more portions of the one or more comments based on criteria associated with each of the keywords. The similarity score for each of the keywords may be compared to a validation threshold and if the similarity score for a subset of the keywords within a trouble shooting ticket exceeds the validation threshold, the trouble shooting ticket may be validated as associated with the incident. If a number of trouble shooting tickets are validated as being associated with the incident exceeds a service outage threshold, an alert may be issued for the service outage.

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 scheduling a meeting are presented. A message comprising a plurality of sentences may be received. A hierarchical attention model may be utilized to identify a subset of sentences of the plurality of sentences that are relevant to a scheduling of the meeting. A subset of words in the subset of sentences that are potentially relevant to scheduling of the meeting may be identified based on relating to at least one meeting parameter. The subset of words may be split into a first group comprising words from the subset of words that are above a meeting relevance threshold value, and a second group comprising words from the subset of words that are below a meeting relevance threshold value. An automated action associated with scheduling the meeting may he caused to be performed.

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.

Abstract: A software agent, that is used to assist in providing a service, receives communications from a set of users that are attempting to use the software agent. The communications include communications that are interacting with the software agent, and communications that are not interacting with the software agent. The software agent performs natural language processing on all communications to identify such things as user sentiment, user concerns or other items in the content of the messages, and also to identify actions taken by the users in order to obtain a measure of user satisfaction with the software agent. One or more action signals are then generated based upon the identified user satisfaction with the software agent.

Abstract: A time aggregation and control system detects when an automated scheduling assistant is invoked to perform a scheduling operation. It detects scheduling characteristics corresponding to the scheduling operation and identifies a time saving value corresponding to the scheduling operation. The time saving value is aggregated over a plurality of different scheduling operations until a time block trigger is detected. A scheduling control signal is generated, to automatically reserve a block of time, based upon the aggregated time saving values.

Abstract: A software agent, that is used to assist in providing a service, receives communications from a set of users that are attempting to use the software agent. The communications include communications that are interacting with the software agent, and communications that are not interacting with the software agent. The software agent performs natural language processing on all communications to identify such things as user sentiment, user concerns or other items in the content of the messages, and also to identify actions taken by the users in order to obtain a measure of user satisfaction with the software agent. One or more action signals are then generated based upon the identified user satisfaction with the software agent.

Abstract: A software agent, that is used to assist in providing a service, receives communications from a set of users that are attempting to use the software agent. The communications include communications that are interacting with the software agent, and communications that are not interacting with the software agent. The software agent performs natural language processing on all communications to identify such things as user sentiment, user concerns or other items in the content of the messages, and also to identify actions taken by the users in order to obtain a measure of user satisfaction with the software agent. One or more action signals are then generated based upon the identified user satisfaction with the software agent.

Abstract: A set of nodes are organized into a graph to represent a workflow to enable the dynamic and directed management of that workflow in a decentralized system. Each node maintains a value necessary for execution of the workflow, and includes code to populate that value. A workflow agent manages the population of the values according to an identified dependency structure for the nodes relative to the workflow. As changes are made to the workflow, the workflow agent ensures that values and dependencies of the nodes stay up-to-date. Each node retains historic values, which enables the workflow agent to query several states of the workflow throughout time as changes are made thereto. The dynamic management of the nodes improves the responsiveness of the system to changes, thereby improving computational efficiency.

Abstract: Linguistic analysis based correlation of distinct events is provided. In examples, trouble shooting tickets may be received over a time period. A linguistic analysis may be performed on one or more portions of the one or more comments using a linguistic model and a similarity score may be computed for one or more keywords within the one or more portions of the one or more comments based on criteria associated with each of the keywords. The similarity score for each of the keywords may be compared to a validation threshold and if the similarity score for a subset of the keywords within a trouble shooting ticket exceeds the validation threshold, the trouble shooting ticket may be validated as associated with the incident. If a number of trouble shooting tickets are validated as being associated with the incident exceeds a service outage threshold, an alert may be issued for the service outage.

Abstract: Linguistic analysis based correlation of distinct events is provided. In examples, trouble shooting tickets may be received over a time period. A linguistic analysis may be performed on one or more portions of the one or more comments using a linguistic model and a similarity score may be computed for one or more keywords within the one or more portions of the one or more comments based on criteria associated with each of the keywords. The similarity score for each of the keywords may be compared to a validation threshold and if the similarity score for a subset of the keywords within a trouble shooting ticket exceeds the validation threshold, the trouble shooting ticket may be validated as associated with the incident. If a number of trouble shooting tickets are validated as being associated with the incident exceeds a service outage threshold, an alert may be issued for the service outage.

Abstract: Linguistic analysis based correlation of distinct events is provided. In examples, trouble shooting tickets may be received over a time period. A linguistic analysis may be performed on one or more portions of the one or more comments using a linguistic model and a similarity score may be computed for one or more keywords within the one or more portions of the one or more comments based on criteria associated with each of the keywords. The similarity score for each of the keywords may be compared to a validation threshold and if the similarity score for a subset of the keywords within a trouble shooting ticket exceeds the validation threshold, the trouble shooting ticket may be validated as associated with the incident. If a number of trouble shooting tickets are validated as being associated with the incident exceeds a service outage threshold, an alert may be issued for the service outage.

Abstract: Service issues predicted by detecting anomalies in an event signal is provided. An application such as a signal analysis application receives an event signal for analysis. The event signal includes events captured during a time period. The event signal is processed to generate a trend line. The trend line includes a best fit line transposed across averages of number of events of each data point across the time period. The number of events of an end data point may be compared to an upper confidence score and a lower confidence score associated with the end data point on the trend line. In response to detecting the number of events of the end data point exceed the upper confidence score, a notification is transmitted to a stakeholder associated with the event signal. The notification may describe a symptom associated with the number of events on the end data point.

Abstract: Service issues predicted by detecting anomalies in an event signal is provided. An application such as a signal analysis application receives an event signal for analysis. The event signal includes events captured during a time period. The event signal is processed to generate a trend line. The trend line includes a best fit line transposed across averages of number of events of each data point across the time period. The number of events of an end data point may be compared to an upper confidence score and a lower confidence score associated with the end data point on the trend line. In response to detecting the number of events of the end data point exceed the upper confidence score, a notification is transmitted to a stakeholder associated with the event signal. The notification may describe a symptom associated with the number of events on the end data point.

Abstract: Concepts and technologies are described herein for providing contextually-aware discovery of solutions. In some configurations, a computing device may receive a request from a tenant. A request may be any type of request, including a service request or any other type of request for information. To process the request, the computing device may also obtain data that associates characteristics with the tenant. For example, one or more resources may maintain a database that includes a tenant identifier, data indicating the size of the tenant, the length of time a tenant has been in service, or any other type of characteristic of the tenant.