In one embodiment, a receipt server includes an acquisition unit and an output unit. The acquisition unit acquires receipt data on a commercial transaction, identified by transaction identification information included in settlement sales data reported from a settlement terminal to a settling agent that assists settlement of the commercial transaction, from a receipt storage unit that stores receipt data generated by the settlement terminal at a time of settlement of the commercial transaction. The output unit outputs information, relating to a purchased commercial product included in the receipt data acquired by the acquisition unit to a settlement server of the settling agent.

A method comprises receiving a route of an aircraft, identifying a plurality of service providers to provide data services for the aircraft based on the route, receiving data from the plurality of service providers associated with the data services, transmitting the data received from the plurality of service providers to the aircraft, determining a total amount associated with all of the data services provided by the plurality of service providers, and transmitting information on the total amount associated with all of the data services provided by the plurality of service providers.

Example aspects include techniques for accurate and expeditious cloud service health communication to customers. These techniques may include determining that a service health incident has customer impact, the service health incident corresponding to an outage of one or more services of a cloud computing platform, identifying a plurality of customers impacted by the service health incident, and predicting, based on the service health incident and one or more other service health incidents, aggregated incident information identifying a plurality of service health incidents associated with the outage of the one or more services. In addition, the techniques may include identifying the one or more services associated with the service health incident, and transmitting, based at least in part on the aggregated incident information and the one or more services, a health notification to the plurality of customers.

An online concierge system trains a machine learning conversion model that predicts a probability of receiving an order from a user when the user accesses the online concierge system. The conversion model predicts the probability of receiving the order based on a set of input features that include price and availability information. For each access to the online concierge system, the online concierge system applies the conversion model to a current price and availability and to an optimal price availability. The online concierge system generates a metric as the difference between the two predicted probabilities of receiving an order.

A computer-implemented method is disclosed. The method includes: receiving transfer parameters associated with a request for a first transfer of resources, the transfer parameters including an identifier of a designated transferor associated with the first transfer; determining that the transferor is eligible to access at least one protected data source based on the transfer parameters; generating a request message for the request including reference data for accessing the at least one protected data source; and providing, to a computing device associated with the transferor, the request message.

Computer-implemented systems and methods are provided for tracking user activity and managing quests. By way of example, a method may include receiving, from a website server, first identity data representing an identity of a user and data identifying a quest activated by the user, the quest comprising one or more activities to be performed at a physical location, and receiving, from at least one reporting device, second identity data representing the identity of the user at the physical location, and activity tracking data in response to the user performing an activity associated with the quest at the physical location. The method may also include identifying the user and the quest activated by the user based on the first identity data and data identifying the quest, further identifying the user and activity data related to the quest based on the second identity data and activity tracking data, and monitoring a progress of the user.

This application relates to systems, methods, devices, and other techniques for utilizing visual reality shopping experience for users.

According to one embodiment, a server includes a storage unit, a communication interface to connect to store servers and customer terminals, and a control unit. The control unit is configured to receive an order from a customer terminal via the communication interface for an item at a store in a plurality of stores at a facility shared by the plurality of stores and output a seat congestion information request to the customer terminal. The seat congestion information request causes the customer terminal to display a request on the customer terminal for an input of congestion information indicating a congestion state of shared seats at the facility. The control unit receives the congestion information from the customer terminal device and tracks the congestion state of the shared seats based on the received congestion information.

The disclosure relates to AI-based machine-learning and natural language modeling to identify semantic similarities between sets of content having natural language text. For example, a system may generate a relevance classification that indicates whether content such as articles are non-specifically relevant to charities without identifying a particular charity. If the content is non-specifically relevant to charities, the system may apply a natural language model to generate sentence embeddings based on the content and determine a level similarity between the sentence embeddings and a query embedding generated from a charity query. The charity query may itself be generated from a full description of the charity through an encoder-decoder architecture with reinforcement learning.

Methods, apparatus, systems, and articles of manufacture are disclosed to determine unique audience size via clustered data. An example apparatus includes memory, machine readable instructions, and processor circuitry to at least one of execute or instantiate the machine readable instructions. The example processor circuitry is to form a first matrix identifying matching and non-matching instances of first values of respective demographics of an audience of media and second values of the respective demographics. Also, the processor circuitry is to normalize the first matrix to generate an account sharing adjustment matrix. Additionally, the processor circuitry is to apply the account sharing adjustment matrix to a vector of one or more counts of impressions of the media to correct for one or more members of the audience that share a user account registered with a database proprietor, the one or more counts of the impressions corresponding to the respective demographics.