Abstract: Systems and methods are described for mitigating errors introduced during processing of user input such as voice input. A query may be derived from processed user input. A performance predictor analyzes the query and uses historical data to predict whether the query will return relevant results if executed. If the query's predicted performance is below a threshold, a query rewriter may identify potential alternatives to the query from a library of “known good” queries. Different analyzers may be applied to identify different sets of alternatives, and machine learning models may be applied to rank the outputs of the analyzers. The best-matching alternatives from each analyzer may then be provided as inputs to a further machine learning model, which assesses the probability that each of the identified alternatives reflects the intent of the user. A most likely alternative may then be selected to execute in place of the original query.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor usage of virtual computing environments. An example method involves obtaining usage records from a probe manager. The example usage records associate users to occurrences of the users consuming a service. The example method also involves determining an association of the user identifiers with respective ones of the business units. The example method also involves creating aggregate usage records for the respective ones of the business units by assigning the usage records to the respective ones of the business units. Additionally, the example method involves transmitting the aggregate usage records to an infrastructure manager, the infrastructure manager to calculate total monetary costs of the service for the respective ones of the business units based on aggregate usage records.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor usage of virtual computing environments. An example method involves obtaining usage records from a probe manager. The example usage records associate users to occurrences of the users consuming a service. The example method also involves determining an association of the user identifiers with respective ones of the business units. The example method also involves creating aggregate usage records for the respective ones of the business units by assigning the usage records to the respective ones of the business units. Additionally, the example method involves transmitting the aggregate usage records to an infrastructure manager, the infrastructure manager to calculate total monetary costs of the service for the respective ones of the business units based on aggregate usage records.

Abstract: Computational methods and systems for detecting cost outliers in various information technology (“IT”) services provided an IT service provider are described. In one implementation, bills of IT generated for each billing period are converted into corresponding cost-flow models with expense nodes. Each expense node represents a cost for a particular IT services purchased during a billing period. The method searches the expense nodes over the billing periods for cost outliers, and rank orders the cost outliers. The method then analyzes the cost outliers in order to identify a possible root cause for each cost outlier. The rank order and possible cost outliers are stored in a data-storage device.