Systems and methods are provided for supplying a video advertisement to a web page or application. A main ad server provides an ecosystem to network ad servers from different ad networks. The main ad server can collect and store information about each of the demand tags associated with each of the network ad servers in a database. The main ad server can then review the database in response to an ad call from a publisher to generate an ordered list of the demand tags that correspond to the ad call. The main ad server can then determine if any of the demand tags in the ordered list has a corresponding video header bidding tag and initiate an auction process for all of the demand tags in the ordered list that have a video header bidding tag. The ordered list of demand tags can then be updated based on the results of the auction process.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving one or more objectives and one or more constraints from a user electronic device of a user; generating a combined objective using the one or more objectives; calculating, using the combined objective, a return per click for an advertisement campaign; determining one or more bids based on (a) the return per click for the advertisement campaign and (b) a return on advertising spend for the advertisement campaign; estimating, using a first predictive algorithm and the one or more bids, an average cost per click; estimating an expected number of clicks for the advertisement campaign based on the average cost per click; determining a total amount used of the one or more constraints for the one or more bids based on the expected number of clicks for the advertisement campaign; and when the total amount used of the one or more constraints for the one or more bids exceeds at least one of the one or more constraints, lowering the one or more bids. Other embodiments are disclosed herein.

A method and system for de-duplicating bids for an advertising request in a real-time bidding online environment includes receiving an ad request from a requestor service and creating a fingerprint based on metadata of the ad request. The fingerprint is compared to pre-existing fingerprints within a database and if no match is found, an auction is conducted for bids from one or more ad buyers for the ad request. If a matching fingerprint is found within the database, the ad request may be designated as a duplicate and not submitted for auction or it may be further processed according to pre-determined criteria to determine whether exceptions are present to allow the ad request to be advanced for auction.

A system and method for creation, distribution and tracking of advertising via electronic networks, enabling creation of advertisements using licensed third party content and placement of said ads at desired network locations, utilizing an auction of ad spaces based on bids placed by advertisers to have their ads displayed at such locations. When a network user/ad viewer requests an ad by clicking or other action, an auction algorithm executes to select the ad to be displayed from those that bid for display at such ad space location and then the ad is composed and delivered to the ad space location by accessing a relational database storing commands that retrieve, assemble and dispatch the licensed ad content. Usage and display of licensed content on designated ad space is tracked to enable cost-per-use charging for both use of licensed content and ad display at the designated ad space.

A system and method for mediated online-advertising providing financially-incentivized, anonymous user-viewing of personalized advertising content through an automated databroker system configured to construct user groups and user group bundles from user profiles and match the user groups and user group bundles with personalized advertiser content received from advertisers in accordance with market stabilizing criteria.

The disclosure provides a method for performing marketing to a telecommunication device and an advertisement server. The method includes: providing a specific advertisement via a specific advertisement carrier, wherein the specific advertisement carrier is disposed at a specific address; in response to determining a specific telecommunication user of a specific telecommunication device has seen the specific advertisement, obtaining an advertising identifier corresponding to the specific telecommunication device; and performing a marketing operation to the specific telecommunication device based on the advertising identifier corresponding to the specific telecommunication device.

Resource allocation includes generating a resource allocation identifier corresponding to a resource allocation request. The resource allocation request pertains to allocation of a resource associated with streaming of an audiovisual content item. The resource allocation identifier comprises a first portion and a second portion, the first portion comprising a key, and the second portion comprising information associated with contextual metadata pertaining to the corresponding resource allocation request. It further includes performing a first transmission of a first message including the resource allocation identifier. The first message including the resource allocation identifier is directed to a first address associated with a first entity. It further includes performing a second transmission of a second message. Transmission of the second message causes transmission of the resource allocation request. The second message is directed to a second address associated with a second entity. The first address and the second address are different. Resource allocation includes receiving a first message comprising a resource allocation identifier. It further includes, at a time subsequent to receiving the first message, receiving a second message comprising a resource allocation request pertaining to allocation of a resource associated with streaming of an audiovisual content item. It further includes matching the resource allocation request with the resource allocation identifier. It further includes, based at least in part on the match, receiving contextual metadata associated with the resource allocation request. It further includes facilitating resource allocation at least in part by using the contextual metadata.

A computer-implemented method for allocation-free control of online campaigns for distributing online content includes receiving a daily content distribution spending budget and one or more response functions, calculating one or more plant gain estimates based on the one or more response functions, calculating a marginal content distribution spending budget based on the daily content distribution spending budget, generating one or more control signals based on the calculated marginal budget and the calculated one or more plant gain estimates, generating a price control signal based on the generated one or more control signals, and calculating a bid for one or more impressions based on the price control signal.

Methods and devices for controlling access to sensitive data stored in a computer system are provided. For at least some data entries in a dataset, each identified by a respective key, an indicator of which zero or more conditions of a plurality of queries are satisfied by that data entry is generated. The keys are grouped into cohorts based on the indicators, at least some of the cohorts comprising keys identifying data entries satisfying the same zero of more conditions. A first output is transmitted to the first computing device comprising an identifier of a first cohort and an indication of a condition which is satisfied by data entries identified by keys in the first cohort. A second output is transmitted to a second computing device comprising an identifier of the first cohort and a set of keys corresponding to the data entries in the first cohort.

Techniques for using machine-learned models to throttle content are provided. In one technique, based on multiple selection events, a distribution of relevance measures is computed, where the relevance measures are associated with the content item selection events. The relevance measures may be generated by one or more machine-learned models. Based on the computed distribution, a threshold relevance measure is computed. Thereafter, a request for content is received over a computer network. In response, a computer system performs, in real-time, multiple steps. For example, an identity of an entity that is associated with the request is identified and, based on that identity, multiple content delivery groups are identified. A relevance measure of one of the content delivery groups relative to the entity is determined and compared to the threshold relevance measure. The content delivery group is selected only after determining that the relevance measure is above the threshold relevance measure.