Systems, methods, and apparatus for utilizing forward market pricing to facilitate operational decisions are disclosed. An example method may include interpreting a compute resource utilization requirement for a task system, and interpreting a behavioral data source, comprising entity behavioral data for an entity associated with the task system. The method may also include forecasting a forward market price for a compute resource in response to the compute resource utilization requirement and the behavioral data source, and, in response to the forward market price, adjusting an operation of the task system or executing a transaction.

Systems, methods, and apparatus for utilizing forward market pricing to facilitate operational decisions are disclosed. An example method may include interpreting a resource utilization requirement for a task system having at least one of a compute task, a network task, or a core task. The method may further include interpreting an automated agent behavioral data source to obtain behavioral data, and operating a machine to forecast a forward market value for a resource in response to the resource utilization requirement and the behavioral data. The method then includes, in response to the forecast of the forward market value for the resource, adjusting an operation of the task system or executing a transaction.

Methods for utilizing forward market pricing to facilitate operational decisions are disclosed. An example method may include interpreting a resource utilization requirement for a task system having at least one of a compute task, a network task, or a core task, and accessing an external provider to provide at least a portion of the compute task, the network task, or the core task. The method may also include interpreting a behavioral data source and operating a machine to forecast a forward market value for a resource in response to a remaining resource utilization requirement and the behavioral data source. The method may then include, in response to the forecast of the forward market value for the resource, adjusting an operation of the task system or executing a transaction.

Performance-based digital content delivery in a digital medium environment is described. Initially, different items of a collection of digital content are delivered to a substantially equal number of users. The collection is then iteratively tested to identify which content item achieves a desired action (e.g., conversion) at a highest rate. During the iterative test, data describing user interaction with the delivered content is collected. Based on the collected data, measures of achievement are determined for the different content items. Measures of statistical guarantee are also computed that indicate an estimated accuracy of the achievement measures. Responsive to determining that a condition for ending the test has not yet occurred, an optimized allocation is computed for delivery of the content by applying one of multiple allocation optimization techniques. The particular technique applied is based on the condition for ending the test and a type of statistical guarantee associated with the test.

A computer-implemented method includes analyzing content associated with a plurality of users, selecting a group of users associated with a topic of the content and generating a class model for the group of users based on the analysis. The computer-implemented method also includes providing new content to the group of users and identifying a leader of the group of users based on relationships defined by the class model and the new content. The computer-implemented method also includes providing a notification to the leader, wherein the notification encourages the leader to engage with the new content.

This specification describes technologies relating to content presentation. In general, one aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving ad information from a seller; generating, using one or more processors, a single conversion ad using the received ad information, where the single conversion ad has an available inventory of one such that only a single conversion of the ad can be performed; transmitting the single conversion ad to one or more potential buyers; receive an input from one of the one or more potential buyers; and notifying the seller of the user input. Other embodiments of this aspect include corresponding systems, apparatus, and computer program products.

Systems and methods for creating pattern awareness and proximal deduction of wireless devices is disclosed. The methods allow wireless awareness among a plurality of wireless signals and the ability of assigning meaning to a group of wireless signals associated with an observing WED, or wireless signal detector and take action based on the meaning.

The disclosed exemplary embodiments include computer-implemented systems, apparatuses, and processes that, among other things, provide a marketplace platform accessed within various application environments, such as a gaming environment associated with a video game. The market platform automatically determines product advertisements that appropriate for presentation within the gaming environment based on an application of trained machine learning and artificial intelligence models to selected elements of input data, and facilitates a purchase of advertised products without a user's exit from the gaming environment by maintaining centralized elements of profile data characterizing the user.

One or more computing devices, systems, and/or methods for isolated budget utilization are provided. A first budget pacing component is assigned to control bidding by a first content serving component for a set of content items. A second budget pacing component is assigned to control bidding by a second content serving component for the set of content items. The first budget pacing component controls the bidding by the first content serving component according to a first portion of a content item budget based upon a traffic share of the first content serving component. The second budget pacing component controls the bidding by the second content serving component according to a second portion of the content item budget based upon a traffic share of the second content serving component.

Social media networking applications, web sites, and services creates implicit relationships between users based on their interest or participation in real-world and optionally virtual or online activities in addition to explicitly defined peer relationships. User profiles, activity entities, and expressions may be associated with metadata to assist in searching and navigation. Metadata is implicitly associated with user profiles, activity entities, expressions, or other data entities based on user behavior using metadata collector. A metadata collector is a poll, survey, list, questionnaire, census, test, game, or other type of presentation adapted to solicit user interaction. A metadata collector is associated with metadata elements. When users interact with a metadata collector, their user profiles and the data entities included in their interactions become associated with the metadata elements of the metadata collector. These metadata element associations may then be used for any purpose.