Systems, methods, and computer-readable media are disclosed for parallel data pool processing and intelligent item selection. In one embodiment, an example method may include determining a first bid request comprising a first user identifier, determining a first set of product identifiers in a first user interaction history of the first user identifier, determining a second bid request comprising a second user identifier, and determining a second set of product identifiers in a second user interaction history of the second user identifier. Example methods may include determining estimated values for one or more product identifiers in the first set of product identifiers and the second set of product identifiers in parallel, and generating respective first and second responses to the first bid request and the second bid request using the estimated values.

A computing device is configured to display content using a set of rules for individual content campaigns. The set of rules are provided with parameters determined from a simulated budget. Simulated bidding traffic is provided. Weighted bid traffic is generated based on evaluating the simulated bidding traffic with the set of rules. Qualified bid requests are provided from using the weighted bid traffic and updates to the parameters of the simulated budget. The qualified bid requests are applied to content servers to secure content slots for displaying content.

A computer-implemented method performed in preparation for a real time bidding process for determining a dynamic floor price of content items viewed by users, the method including collecting page information and information related to multiple users over time, receiving a view request to view a specific content item by a computerized device operated by a specific user, collecting real-time information concerning the specific user and the specific content item after receiving the view request to view the specific content item, determining the dynamic floor price for the specific content item for a specific user in a specific time slot based on the real-time information, the page information and the information related to multiple users over time and issuing an ad request for an ad impression to advertisement demand sources that includes the specific content item, the specific time slot and the specific ad placement.

One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A request for content may be received. A second plurality of content items associated with a plurality of rankings may be selected from a plurality of content items based upon a plurality of bid values. A quantity of content items of the second plurality of content items may be greater than a quantity of content items associated with the request for content. One or more ghost content items associated with one or more rankings of the plurality of rankings may be identified. A ghost impression indicator associated with a ghost content item of the one or more ghost content items may be stored based upon a determination that a ranking, of the one or more rankings, associated with the ghost content item matches a second ranking of a presented content item.

Aspects of the subject disclosure may include, for example, receiving an ad call associated with an ad space available in media content that is being presented at an end user device, and conducting auctions with a group of bidders that are identified based on an analysis of line items and a curated deal, where the auctions include a curated deal auction based on the curated deal in which a broker aggregates curated deal inventory across a plurality of sellers including a seller of the ad space, and where the curated deal inventory includes the ad space. Bids can be obtained from the auctions to determine a winning bid. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, determining classes from a corpus based on topic modeling, data clustering and unsupervised learning. Labels are determined for each of the classes and trained models are generated for each of the classes by assignment of a plurality of textual documents to labels based on a highest number of matches. A raw textual document can be tokenized and stop words removed. A corresponding one of the trained models can be selected according to a class that is applicable to subject matter of the raw textual document. The processed document can be assigned to a target label based on a highest number of matches of words. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, receiving a bid request that indicates a television channel associated with a video stream requested by an end user device and that includes ad space information associated with an ad space of the video stream, where the video stream being requested is an Over-The-Top (OTT) streaming service that provides scheduled content. Context information can be accessed according to the television channel and according to a time associated with the ad space, where the context information describes the video stream and is generated by a context server. An auction is performed to obtain bid responses, where the auction provides bidders with context data that is representative of at least a portion of the context information, and where selection of the candidate bid responses enables a determination of a creative for the ad space of the video stream. Other embodiments are disclosed.

A method for celebrity-based advertising includes storing, in a server, a likeness of subject and a corresponding booking that includes parameters outlining availability of the subject for digital advertising. The method further includes receiving or creating, by the server, a pitch that falls within the parameters of the booking, the pitch corresponding to the subject. The method further includes receiving, by the server and from a first user device, a first image of the likeness of the subject or another likeness of the subject. The method further includes determining, by the server, that the image matches the likeness of the subject. The method further includes transmitting, by the server, the pitch to the first user device to be output by the first user device.

Merchants create ecommerce-enabled ad units advertising items offered by the merchants. The ad units contain functionality enabling customers to purchase the items by interacting with the ad units. The ad units have associated bid prices that the merchants agree to pay for sales through the ad units. The merchants provide the ad units to a broker. The broker publishes the ad units on web pages provided by publishers as comparison shop ad units that contain multiple ad units and functionality for navigating among them. A customer receiving a web page interacts with an ad unit to purchase the item. During the interactions, the broker dynamically updates the ad unit to conduct the transaction.

Systems, methods, and computer-readable media that may be used to modify a voice action system to include voice actions provided by advertisers or users are provided. One method includes receiving electronic voice action bids from advertisers to modify the voice action system to include a specific voice action (e.g., a triggering phrase and an action). One or more bids may be selected. The method includes, for each of the selected bids, modifying data associated with the voice action system to include the voice action associated with the bid, such that the action associated with the respective voice action is performed when voice input from a user is received that the voice action system determines to correspond to the triggering phrase associated with the respective voice action.