Abstract: A computer implemented method and system for a recommendation engine utilizing progressive labeling and user context enrichment.

Abstract: A server for providing a generic actor system container application comprising: status and control graphical user interfaces, a listener service, a cluster manager, an actor registry and discovery service, a system configurator, a plurality of handles, a plurality of listeners, and a plurality of generic actors, wherein the generic actor system container application is configured to: receive information associated with a plurality of customized domain specific actors; receive a plurality of domain specific connection information; generate the plurality of domain specific actors based on the information associated with the plurality of customized domain specific actors; register the plurality of domain specific actors; and execute and monitor a domain specific actor system using the domain specific actors based on the domain specific connection information.

Abstract: A method for the reorganization of messages in queuing systems is disclosed. The method comprising receiving a statement to reorganize one or more messages within an ordered data structure; translating the statement into a first set of instructions for identifying one or more messages on which to perform one or more operations, a second set of instructions for performing the one or more operations on the identified one or more messages, and a third set of instructions for storing, in a memory, the identified one or more messages after the one or more operations have been performed; executing the first set of instructions, the second set of instructions, and the third set of instructions on each message in the ordered data structure; and transmitting the operated upon messages.

Abstract: A server for providing a generic actor system container application comprising: status and control graphical user interfaces, a listener service, a cluster manager, an actor registry and discovery service, a system configurator, a plurality of handles, a plurality of listeners, and a plurality of generic actors, wherein the generic actor system container application is configured to: receive information associated with a plurality of customized domain specific actors; receive a plurality of domain specific connection information; generate the plurality of domain specific actors based on the information associated with the plurality of customized domain specific actors; register the plurality of domain specific actors; and execute and monitor a domain specific actor system using the domain specific actors based on the domain specific connection information.

Abstract: A method for the reorganization of messages in queuing systems is disclosed. The method comprising receiving a statement to reorganize one or more messages within an ordered data structure; translating the statement into a first set of instructions for identifying one or more messages on which to perform one or more operations, a second set of instructions for performing the one or more operations on the identified one or more messages, and a third set of instructions for storing, in a memory, the identified one or more messages after the one or more operations have been performed; executing the first set of instructions, the second set of instructions, and the third set of instructions on each message in the ordered data structure; and transmitting the operated upon messages.

Abstract: Embodiments of the present invention are directed to dynamically allocating shared cloud-based resources among multiple parties. A cloud provider provides a quota service that implements two quota allocation models: a reserved model and a hybrid model. The reserved model allows for reserved quota allocations, and the hybrid model allows for both reserved and fair use quota allocations. Quota trees are used to track resource usage and to ensure usage remains within specified quota limits. While the cloud provider is able to efficiently manage its resources, an organization that uses the cloud provider's resources does not need to purchase as many resources, such as space, bandwidth, memory usage, processing power, or other unit of work.