Methods, systems, and computer program products are provided for presenting an option to have a content item provided to users based on one or more interests. One example method includes providing filtering parameter selection controls, receiving a filtering parameter selection, receiving at least one term corresponding to the one or more interests, and presenting suggestions based on the received term. An estimated number of users having interests matching the suggestions and having user attributes matching the received filtering parameter selection is determined, and the estimated number of users is presented for at least one of the suggestions. A selection of at least one of the suggestions is received, and the content item is delivered to users having interests matching the selected suggestion and having user attributes matching the filtering parameter selection.

A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. The sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. The first or second activity information can include a cookie, which can be used to identify a node in a social graph as being representative of a particular person or user. When a match is not found, a fingerprinting approach can be performed using attributes, such as device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, or behavioral patterns.

A system for auctioning a vehicle through the internet and through the collaboration of a vehicle dealer and an auction house. The system includes a vehicle dealer having their own website, and an auction house having their own website. Through collaboration between the vehicle dealer and the auction house various other cobranded websites are presented for the auction of vehicles. These cobranded websites are accessible either through the vehicle dealer website or the auction house website, and are either hosted on the vehicle dealer website or the auction house website. In this way, greater access is provided to the vehicle auction while maintaining the continuity of experience for the buyer, thereby increasing sales and internet traffic.

The present disclosure relates to systems, non-transitory computer-readable media, and methods to generate sketches for clearing-bid values and bid-success rates based on multi-dimensional targeting criteria for a digital-content campaign and dynamically determine predicted values for the digital-content campaign based on the sketches. To illustrate, the disclosed systems can use a running-average-tuple-sketch to generate tuple sketches of historical clearing-bid values and tuple sketches of historical bid-success-rates from historical auction data. Based on the tuple sketches, the disclosed systems can determine one or more of a predicted cost per quantity of impressions, a predicted number of impressions, or a predicted expenditure for the digital-content campaign—according to user-input targeting criteria and expenditure constraints.

One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.

Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.

Embodiments of the invention provide a computer-implemented method of participating in a web-based content provision process, e.g. an ad-bidding process for proposing an ad to serve for an ad impression. The method can include recording physical behavioural information, e.g. emotional state, attentiveness, gaze tracking, etc., to infer or further refine a user profile for a user or to establish or further refine a target profile for a piece of media content, e.g. an advertisement. A quantitative indicator can be obtained by comparing user profiles with target profiles, which can be used to automate the content provision process. The process can use a plurality of preset user types and a plurality of preset ad target types, whereby each user is allocated to one or more of the preset user types and each ad is allocated to one or more of the preset ad types.

Systems, methods, and devices relating to automatic facial detection and age and/or gender determination. An image source provides a sequence of images of an audience. Each image is analyzed to detect each face in the image. Specific features of each face are then extracted and, from these features, the gender and/or age of the face is determined by referring to previous determination results. Once the age and/or gender of the audience has been determined, a server can then select which advertisement spots can be presented to the audience. This may be done by having the server request access to a database of available advertising spots, submits specific parameters as the basis for the selection of the advertisement. Image source, image processing subsystems, advertisement displays and advertisements databases can be collocated or distributed over various network resources.

Methods, systems, and apparatus, including computer program products, for Out-of-home and/or home targeted interactive content, infomercial and advertizing is based on generating and/or receiving user identifier/s for each individual person from the audience, viewers and/or users (“User”) in the vicinity of out-of-home electronic or not displays such as prints, banners and/or video billboards of any kind and/or home entertainment such as computer monitors, computers connected to TV sets, smart TVs and/or TV sets stationary or moving (“Display”). User identifier is generated based on retrieved and/or received unique identifier and/or associated data (e.g., user, Smartphone number, MAC addresses, location, etc.) from the User's electronic devise/s, for example, smartphone, wearables and/or implantables in the vicinity of the Display. User identifier and/or associated data can be used, for example, for programmatic bidding, generating inventory and/or bid request message to be published on advertising and/or financial exchange/s to serve creatives on the associated Display, tracking, tagging, targeting, cross-device retargeting, conversion, compute advertising metrics and universal attribution with fraud detection and prevention. Provide User/s with methods to interact with the Display via their electronic devices such as smartphones for additional information, redirect to the associated content landing page and to ultimately convert the User.

Systems and methods are provided for facilitating media playback in online auctions. A method may include detecting an indication of an auction event associated with an online vehicle auction for a first vehicle. The method may also include determining current auction information associated with the online vehicle auction. The method may further include determining auction event information associated with the auction event. Additionally, the method may include identifying, based at least in part on the current auction information and the auction event information, one or more media files for playback on a bidder device. The method may also include transmitting, to the bidder device in response to the indication of the auction event, the one or more media files for playback on the bidder device according to a determined sequence, which may result in acoustic output of one or more auctioneer phrases.