An escrow agent for verifying attribution of conversions includes a processing element and a non-transitory memory. The non-transitory memory is coupled to the processing element and stores instructions for verifying attribution of conversions. The instructions, when executed, cause the processing element to receive impression information from a plurality of digital advertising servers, receive attribution information from an attribution server for attributed conversions, verify the attribution information responsive to the impression information and attribution information, and send verified attribution information to a client system for attributing conversions to the plurality of digital advertising servers.

Systems and methods are disclosed for determining an estimate of available user impressions on a network, comprising receiving a request for an estimate of available user impressions for viewing one or more media elements on a network, the request comprising one or more viewer demographic group limitations. A request may be received to include deterministic users and probabilistic users in the estimate of available user impressions. A number of deterministic users may be determined based on query results from a deterministic user data set. A number of probabilistic users may be determined based on query results from a probabilistic user data set, and the estimate of available user impressions may be determined based on the number of deterministic users and the number of probabilistic users.

A computerized method and apparatus for evaluating content on a computer network. The method includes obtaining a quality score of content configured for display with a web page, wherein the quality score is based at least in part on keywords associated with the content and either a search query or metadata associated with the web page. The method also includes identifying a user metric of a computing device associated with the search query or the metadata. The method further includes generating an adjusted quality score of the content based on the quality score and the user metric. The method also includes selecting a parameter for an auction based on the adjusted quality score, wherein the parameter indicates a relation between a bid value based auction and a content quality based auction.

A digital license plate with an associated payment and information handling system is described. The payment system allows for automated payment for parking that includes sending authorization to pay parking related payments to a payment authority, with authorization at least partially incorporating information stored in the digital license plate.

Methods, apparatus, systems and articles of manufacture to monitor media presentations are disclosed. An example method includes providing a software development kit (SDK) to an application developer. The SDK is to enable the application developer to create a monitoring enabled application. A panelist identifier is transmitted in response to a request from a registrar executed by the media device. The request includes demographic information associated with a user of the media device. The panelist identifier is stored in a shared memory of the media device and is accessible to the monitoring enabled application. The monitoring enabled application is to collect data if the panelist identifier is in the shared memory and to disable collection of the data if the panelist identifier is not in the shared memory. The data is collected from the monitoring enabled application.

An online system presents a scrollable advertisement unit including multiple advertisements to a user. The scrollable advertisement unit presents one or more advertisements in a display area, and allows a user to navigate through the advertisements in the scrollable advertisement unit to display different advertisements in the display area. One or more rules for crediting an impression to an advertisement in the display area are applied, and a tracking mechanism associated with the advertisement in the display area is loaded if at least one rule is specified. Loading the tracking mechanism identifies an impression of its associated advertisement.

The present application discloses a method for providing promotion content. A server provides to a client device media content and a sequence of closed caption (CC) messages that are synchronized with the media content. Two consecutive CC messages are separated by a blank duration that is marked by a blank mark and lasts for a predetermined length of time. The client device is configured to detect the blank mark and generate a request for promotion content that includes at least a user identification for identifying a user of the client device. Upon receiving the promotion content request, the server determines user preferences associated with the user identification, and further identifies a promotion content item according to the user preferences. The promotion content item is provided to the client device for concurrent display with the media content during the blank duration between the corresponding two consecutive CC messages.

In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.

In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.

In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.