A media presentation and distribution system communicatively coupled to a client device is provided. The client device receives a media stream from the media presentation and distribution system via a network. The media stream includes media content and one or more tags. The client device further identifies in the received media content, the one or more tags, which corresponds to the overlay-graphic items. The client device further identifies candidate time-periods in the media content based on the one or more tags in the media content. At least one presentation attribute for the overlay-graphic items is identified based on the one or more tags in the media content. The client device further presents the overlay-graphic items at the candidate time-periods on the media content based on a degree of correlation between the identified tag in the media content and a corresponding context for the media content at the candidate time-period.

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-er-use charging for both use of licensed content and ad display at the designated ad space.

One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.

Techniques for presenting a content item with a media item are described. The techniques include receiving user input indicating a placement preference for a content item to be presented with a media item. The placement preference indicates a presentation preference of the content item relative to presentation of the media item. The placement preference is used to influence selection of a media item with which the content item is to be presented.

Methods, systems and computer program products for submitting a network proxy bid and replacing the network proxy bid with an actual bid associated with advertisement placement are described. In some implementations, instead of submitting a static bid, an advertiser can submit a network proxy bid to an advertising exchange. A network proxy bid can indicate to the advertising exchange that the advertiser wishes to receive a call back from the advertising exchange when an impression matching targeting criteria specified by the advertiser becomes available. The advertiser then can calculate and submit an actual static bid to replace the network proxy bid in response to the call back.

Systems and methods are provided for presenting information about discrete geographical areas and the use of such information by content providers to facilitate delivery of targeted or geographically relevant content to information playback devices located in one or more particular discrete geographical areas. Data (e.g., contextual, behavioral, predictive, trending, geo-consumer patterns) can be collected and associated with relevant virtual cells within a grid. A portal can be provided to enable content provider to search the cells based on customized campaigns to identify trends, interest, patterns and opportunities. Such information can facilitate informed geo-targeting decisions and consumer understandings for business of all sizes and sectors in order to deliver more relevant content to information playback devices within selected cells according to customized settings configured by the content provider.

Automatically collecting advertisement bidding order by automatically accessing at least one Internet content site and presenting the Internet content site with at least one virtual user data and an at least one of IP address representing a geographic location of the virtual user. In response, receiving from the Internet content site advertisement content, and bidding data. Presenting the advertisement bidding data to a user, and/or storing the advertisement bidding data.

A digital ad-buying platform uses counterfactual-based incrementality measurement by implementing randomization and/or a correction for auction win bias to avoid the need to identify counterfactual winner types in the control group. This approach can estimate impact at the individual consumer level. Confidence levels can be determined using Gibbs sampling in the context of causal analysis in the presence of non-compliance.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for presenting content items. In one aspect, a method includes identifying an opportunity to present a content item at a device and in a manner that precludes a user from accessing content of one or more applications executing on the device. Data relating to a status of each of the one or more applications are identified. A level of urgency for a user to access content of the one or more applications is determined based on the data. A response to the opportunity to present a content item is selected based on the level of urgency for the user to access content of the one or more applications. The response is selected from a first response that causes presentation of the content item and a second response that precludes presentation of the content item.

A method of adjusting a resource competition threshold for qualifying resource competition participants in resource competition is described. Processing circuitry of an apparatus obtains first competition data associated with a first time period, obtains a first optimal threshold according to the first competition data, and set the resource competition threshold according to the first optimal threshold. The processing circuitry obtains second competition data associated with a second time period, and obtains a second optimal threshold according to the second competition data. When a difference between the second optimal threshold and the resource competition threshold is greater than a difference threshold, the processing circuitry obtains third competition data and updates the resource competition threshold according to the third competition data.