Abstract: The present disclosure relates to system and techniques for enabling provisioning of cloud services for a client in an isolated yet scalable manner. In some embodiments, various computing resources are implemented within a cell (a self-sufficient unit). A number of cells are generated for a service or a group of services and distributed across a number of computing devices. Various cells may be generated that each pertain to a different aspect, or particular functionality, of the service. In some embodiments, cells providing various functionality for the service are implemented and distributed across different computing devices.

Abstract: The present disclosure relates to system and techniques for enabling provisioning of cloud services for a client in an isolated yet scalable manner. In some embodiments, various computing resources are implemented within a cell (a self-sufficient unit). A number of cells are generated for a service or a group of services and distributed across a number of computing devices. Various cells may be generated that each pertain to a different aspect, or particular functionality, of the service. In some embodiments, cells providing various functionality for the service are implemented and distributed across different computing devices.

Abstract: The present disclosure relates to system and techniques for enabling provisioning of cloud services for a client in an isolated yet scalable manner. In some embodiments, various computing resources are implemented within a cell (a self-sufficient unit). A number of cells are generated for a service or a group of services and distributed across a number of computing devices. Various cells may be generated that each pertain to a different aspect, or particular functionality, of the service. In some embodiments, cells providing various functionality for the service are implemented and distributed across different computing devices.

Abstract: Target audience content interaction techniques are described. In one or more implementations, a plurality of content is quantified by one or more computing devices as a content feature representation for each of the plurality of content. A plurality of content feature clusters are generated by the one or more computing devices based at least in part on similarity of the content feature representations, one to another. Content cluster interaction data is also created by the one or more computing devices that describes interaction of each of a plurality of users with the plurality of content. A plurality of user interaction clusters are calculated from the content cluster interaction data by the one or more computing devices based at least in part on similarity of the content cluster interaction data of the plurality of users, one to another. The calculated plurality of user interaction clusters are employed by the one or more computing devices to determine content preferences of a target audience.

Abstract: Target audience content interaction techniques are described. In one or more implementations, a plurality of content is quantified by one or more computing devices as a content feature representation for each of the plurality of content. A plurality of content feature clusters are generated by the one or more computing devices based at least in part on similarity of the content feature representations, one to another. Content cluster interaction data is also created by the one or more computing devices that describes interaction of each of a plurality of users with the plurality of content. A plurality of user interaction clusters are calculated from the content cluster interaction data by the one or more computing devices based at least in part on similarity of the content cluster interaction data of the plurality of users, one to another. The calculated plurality of user interaction clusters are employed by the one or more computing devices to determine content preferences of a target audience.

Abstract: User interest learning through hierarchical interest graph techniques are described. In one or more implementations, each of a plurality of categories in a directed hierarchical interest graph are assigned a distance value which represents a shortest distance in the directed hierarchical interest graph from a root category to the category. A list of keywords is formed from user data that denotes a corresponding said category and frequency of the category. A maximum of the frequencies amongst the plurality of categories is determined and a score is calculated for each of the keywords based on the frequency of the category, the maximum of the frequencies, and the distance value for the keyword. Increments of scores may be propagated from child categories to parent categories in the hierarchical interest graph such that greater weighting is given to child categories that are less abstract than parent categories in the directed graph.