A conversion timing model is model is configured to predict a likelihood of conversion based on an entity's elapsed time since a qualified entry event and based on a funnel state. The conversion timing model is constructed based on a distribution of the conversion timespans of converters. A notification of an opportunity to expose a candidate entity to networked content is received. A time-based likelihood of conversion for the candidate entity is determined by applying the conversion timing model to the elapsed time. A response to the notification based on the likelihood of conversion for the candidate entity is prepared based on the time-based likelihood of conversion and based on the funnel state. Timely responses may include the selection of customized content or bid values.

Aspects of the subject disclosure may include, for example, embodiments for determining a media profile for media content. The media profile comprises a media metric for each of a plurality of portions of the media content. Further, embodiments include determining a price for advertising associated with the media content. In addition, embodiments include identifying an advertisement profile for each of a plurality of advertisements. The advertisement profile comprises an ad metric for each of a plurality of portions of an advertisement. Also, embodiments include selecting a first advertisement associated with a first advertisement profile from the plurality of advertisements according to the media profile, the first advertisement profile, and the price for the advertising associated with the media content. Further, embodiments include providing the first advertisement to be presented with the media content at a playback device. Other embodiments are disclosed.

A system is provided for concurrent presentation of non-programming media assets with programming media content at a client device. The client device receives a response for occurrence of an event opportunity point from the media presentation and distribution system based on a selection criteria for the event opportunity point. A display view of the client device is modified, and a non-programming media asset is presented from a second media stream for a defined duration and different version of the programming media content in first partition, concurrently with the programming media content over second partition. The different version of the programming media content corresponds to the programming media content encoded based on a region within the modified display view allocated to the first partition. The presentation is based on user preference for specific item in the programming media content and user selection of the non-programming media asset displayed in past engagement.

Aspects of the subject disclosure may include, for example, determining an ad play list for an Over-The-Top video stream requested by an end user device based on a price and/or a category of a creative derived from auctions with multiple Supply-Side Platform servers. The ad play list can be determined for the ad pod according to business rules, which can include a yield policy based on increasing revenue for a publisher of the video stream, and/or which can include a competitive separation policy enforced based on the category for bid responses. Other embodiments are disclosed.

Embodiments of the present invention provide a system for generating and displaying tailored advertisements in a mixed reality environment. The system is configured for continuously identifying one or more objects in a mixed reality environment, identifying the one or more objects match advertising targets, generating a tailored advertisement, transmitting the tailored advertisement to the user device, causing the user device to display the tailored advertisement, determining that the user is interacting with the tailored advertisement, and capturing one or more metrics associated with the interaction of the user with the tailored advertisement.

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 a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction 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. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, 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 positive signal probabilities.

A computer-implemented method for improved ticket purchasing/selling process using a ticketing system. The purchasing process of tickets for a user can be facilitated by a web interface having an event selection menu configured to display one or more events having tickets available for purchase. Available inventories for tickets to one or more events can be displayed on an interactive venue map of the web interface. The user can choose desired seats for purchase via the venue map. Additional menus can facilitate the ability for a user to compare show dates, showtimes, and seating availability across different events. The ticketing system can also be configured to collect and process customer data through tracking pixels configured within the one or more pages of the web interface. Subsequently, bidding on digital marketing and advertisement can be conducted using the gathered customer data.

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 the 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 request for a page is received. The page is provided at least in part by determining dynamically a content element for the page. An auction to determine a winning bid is conducted prior to providing the page in response to the request and the content element determined based at least in part on the auction winner.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatically determining parameter values that control or affect provision of content by a content platform. In one aspect, evaluation points are identified for a parameter. Each evaluation point includes an evaluated parameter value of the parameter and a metric value of a metric corresponding to the provision of digital components by the content platform. A first model is generated using the set of evaluation points. A second model is generated based on the first model and an acquisition function that is based on mean values and confidence intervals of the first model and a configurable exploration weight that controls a priority of exploration for evaluating the parameter. A next parameter value to evaluate is determined from the second model and the content platform is configured to use the next parameter value to provide digital components.