Abstract: A device, system and method for controlling memory usage associated with an intermediation engine for a virtual platform is provided. The engine determines that, within the platform, an exchange has occurred of a first data record for a first amount of a first electronic currency associated with the platform, the first data record associated with a computing device external to the platform. The engine: exchanges the first amount for a second data record associated with the platform; maintains, at a first memory, an indication of the second data record; exchanges, external to the platform, the indication of the second data record for a second amount of a second electronic currency used external to the platform; transfers, external to the platform, a portion of the second amount to a second memory associated with the computing device; and clears the first memory of the second data record indication.

Abstract: A device, system and method for secure assistive handling of electronic content is provided. A computing device trains one or more machine learning engines using account profile(s) as training data, the account profile(s) indicative of previous content selected or accessed in association with the account profile(s). After training the machine learning engine(s), the computing device receives, via one or more of a communication interface and a human-machine interface, criteria for selecting content, and searches for content that meets the criteria, using one or more of the communication interface, the machine learning engine(s), and the human-machine interface. The computing device receives, via one or more of the communication interface and the human-machine interface, the content that meets the criteria, and filters, via the machine learning engine(s), the content to generate filtered content according to the account profile(s). The computing device controls an output device to output the filtered content.

Abstract: A device, system and method for more efficiently controlling client devices to provide common content is provided. A computing device: determines that avatars, associated with client devices interfacing with a virtual platform, are within a given distance of each other and/or located in a common area of the platform; and accesses respective associated data comprising: respective static data associated with users of the devices, and/or respective dynamic data indicative of orientation of the avatars within the platform and/or interactions of two or more of the avatars within the platform. The computing device determines, from the data: avatar subset associated with respective content, the subsets each including two or more of the avatars. The computing device causes respective devices, associated with the subsets, to provide the respective content in association with the subsets, such that two or more of the respective devices associated with a same subset provide respective common content.

Abstract: A device, system and method for implementing a computing resource optimization engine is provided. A computing device allocates in a memory, a virtual geographic whitespace within an electronic map of a metaverse publisher platform. The computing device receives, in the memory, an account profile associated with a client device accessing the electronic map in association with the virtual geographic whitespace. The computing device selects an interactive environment, of a plurality of interactive environments, based on the account profile. The computing device controls the metaverse publisher platform to generate the interactive environment within the virtual geographic whitespace for an avatar associated with the account profile while the avatar is associated with the virtual geographic whitespace.

Abstract: The present specification provides a content normalization server and method. The specification can have particular application to client devices with augmented or virtual reality hardware that interact with different platforms with metaverse capabilities. Rich experiences are provided on client hardware while making efficient use of available processing, memory and communication resources.

Abstract: The present specification provides, amongst other things, a computing resource Intermediation engine and method that can select and generate secondary content based on one or more demographic parameters, secondary content options and engagement ratings for those secondary content options.

Abstract: A method in a computing device of adjustment of operational resources based on external events includes: retrieving input data from at least one data source external to the computing device; extracting, from the input data, an event detection record including a time period associated with an event, a location associated with the event, and an impact direction associated with the event; retrieving, based on the time period and the location, a set of operational resource data; generating, based on the event detection record and the set of operational resource data, an impact magnitude associated with the event; selecting, based on the impact direction and the impact magnitude, a supplier of the operational resources; and transmitting a notification to a computing device associated with the selected supplier, the notification including the event detection record.

Abstract: The present specification provides a multiplatform virtual retail store engine. The specification can have particular application to client devices with augmented or virtual reality hardware that interact with different platforms with metaverse capabilities. Rich experiences are provided on client hardware while making efficient use of available processing, memory and communication resources. Embodiments discuss the provision of a single retail store model which is dynamically adapted for generation across the plurality of different platforms according to the different metaverse capabilities.

Abstract: The present specification provides a multiplatform virtual retail store engine. The specification can have application to client devices with augmented or virtual reality hardware that interact with different platforms with metaverse capabilities. Rich experiences are provided on client hardware while making efficient use of available processing, memory and communication resources. Embodiments discuss the provision of a single retail store model which is dynamically adapted for generation across the plurality of different platforms according to the different metaverse capabilities. Embodiments also discuss include ranking of the same user across different accounts on different metaverse platforms. Embodiments discuss the normalization of formatting and content electronic messages representing currencies and other instruments of exchange across different platforms.

Abstract: The present specification provides a multiplatform virtual retail store engine. The specification can have application to client devices with augmented or virtual reality hardware that interact with different platforms with metaverse capabilities. Rich experiences are provided on client hardware while making efficient use of available processing, memory and communication resources. Embodiments discuss the provision of a single retail store model which is dynamically adapted for generation across the plurality of different platforms according to the different metaverse capabilities. Embodiments also discuss include racking of the same user across different accounts on different metaverse platforms.

Abstract: The present specification provides a content normalization server and method. The specification can have particular application to client devices with augmented or virtual reality hardware that interact with different platforms with metaverse capabilities. Rich experiences are provided on client hardware while making efficient use of available processing, memory and communication resources.

Abstract: Methods, methods, systems, and computer program products for implementing an optimization process and simulation process to predictively allocate nodes in a queue. A first number of tasks to be processed in a task queue within a current time interval is determined. A second number of tasks from the task queue that are unprocessed after a time interval that immediately precedes the current time interval is determined. A resource allocation constraint for each resource is determined. A subset of the number of nodes to be assigned to each resource in the time interval is determined based on the first number of tasks, the second number of tasks, and the resource allocation constraint for each resource. A resource allocation schedule, which includes the determined subset of the number of nodes assigned to each resource, is provided to a resource allocation demand server.

Abstract: Virtualization methods and systems for optimizing the availability of items in an inventory of items in a reservation system, wherein the items are classified into item types and an item type is defined by a requestable set of at least one characteristic. Reservations may be received for a set of at least one characteristic that is a subset of an item type. After a reservation has been accepted, all the availabilities of the requestable sets of at least one characteristic in the inventory are updated. The reservation system may be a hotel reservation system and item types may be hotel room types or other bookable products. The reservation system may be a flight reservation system and item types may be bookable places on flights.

Abstract: Computer-implemented methods of providing personalized recommendations to a user of items available in an online system, and related systems. First-level features including context features are computed based upon context data. A first-level machine learning model is then evaluated using the first-level features to generate predictions of user behavior in relation to a plurality of individual items available via the online system. A list of proposed item recommendations is constructed based upon the predictions. Second-level features are computed based upon the context data and list features based upon the list of proposed item recommendations and the corresponding predictions generated by the first-level machine learning model. A second-level machine learning model is evaluated using the second-level features to generate a prediction of user behavior in relation to the list of proposed item recommendations.

Abstract: Virtualization methods and systems for optimizing the availability of items in an inventory of items in a reservation system. The items are classified into item types and an item type is defined by a requestable set of at least one characteristic. Reservations may be received for a set of at least one characteristic that is a subset of an item type. After a reservation has been accepted, all the availabilities of the requestable sets of at least one characteristic in the inventory are updated. The reservation system may be a hotel reservation system and item types may be hotel room types or other bookable products. The reservation system may be a flight reservation system and item types may be bookable places on flights.

Abstract: Virtualization methods and systems for optimizing the availability of items in an inventory of items in a reservation system, wherein the items are classified into item types and an item type is defined by a requestable set of at least one characteristic. Reservations may be received for a set of at least one characteristic that is a subset of an item type. After a reservation has been accepted, all the availabilities of the requestable sets of at least one characteristic in the inventory are updated. The reservation system may be a hotel reservation system and item types may be hotel room types or other bookable products. The reservation system may be a flight reservation system and item types may be bookable places on flights.

Abstract: Computer-implemented methods of providing personalized recommendations to a user of items available in an online system, and related systems. First-level features including context features are computed based upon context data. A first-level machine learning model is then evaluated using the first-level features to generate predictions of user behavior in relation to a plurality of individual items available via the online system. A list of proposed item recommendations is constructed based upon the predictions. Second-level features are computed based upon the context data and list features based upon the list of proposed item recommendations and the corresponding predictions generated by the first-level machine learning model. A second-level machine learning model is evaluated using the second-level features to generate a prediction of user behavior in relation to the list of proposed item recommendations.

Abstract: Virtualization methods and systems for optimizing the availability of items in an inventory of items in a reservation system. The items are classified into item types and an item type is defined by a requestable set of at least one characteristic. Reservations may be received for a set of at least one characteristic that is a subset of an item type. After a reservation has been accepted, all the availabilities of the requestable sets of at least one characteristic in the inventory are updated. The reservation system may be a hotel reservation system and item types may be hotel room types or other bookable products. The reservation system may be a flight reservation system and item types may be bookable places on flights.

Abstract: Methods, systems, and computer program products for optimizing schedules for a plurality of flights in a network of flights. the schedules for the flights may be received. In general, the schedules indicate, for each flight, a departure point, an arrival point, a departure time, and an arrival time. The schedules may be globally optimized to identify one or more schedule adjustments for one or more of the flights that results in an increase in a schedule connection value associated with the schedules, where the global optimization is based at least in part on one scheduling rule that constrains combinability of the flights in the network of flights.

Abstract: The method according to a preferred embodiment of the present invention allows managing an inventory of items where a disconnection has been done between the physical item (as offered by a provider) and the marketing offering (which availability and price will be requested by a customer). A physical item can thus be marketed in several marketing offers, and a booking in one of those marketing offers is not directly assigned to a physical item but is allowed to “float” between them, so as to maximize the availability. The method according to a preferred embodiment of the present invention allows multi-days inventory containing more marketing products than physical ones. A preferred embodiment of the present invention provides the possibility to choose between a strong continuity for the bookings (the booking will be refused if it can not be placed continuously for the whole duration of its stay), or a softer continuity that allows possible changes of room type during the stay, while minimizing their numbers.