According to an implementation, a method for digital information retrieval in a social media platform includes transmitting, over a network, information to render a timeline of social content for a user of a client application. The timeline of social content includes messages posted on the messaging platform by user accounts that are connected to a user account of the user in a connection graph. The method includes computing, using a machine-learning algorithm inputted with relevance signals, a relevance level between the user account of the user and a user account not linked to the user account of the user in the connection graph, and transmitting information about a profile of the user to a computing device associated with the user account not linked to the user account of the user in response to the relevance level being greater than a threshold level.

Disclosed is an on-line advertisement method using an advertisement website. An on-line advertisement method according to an embodiment of the present invention provides an advertisement available to a user terminal at a current position of a user terminal which accesses an advertisement website.

Systems and methods that provide electronic bidding on digital advertising placed on non-personal digital devices in public or semi-public settings and enable subsequent consumer actions taken on other media channels and devices to be attributed to such advertising in digital ad buying systems.

A device's location and an identifier corresponding to the device are received. The device's location is privatized by mapping it to landmarks proximate to the device's location, storing the proximate landmarks in association with the device's identifier, and discarding the received location data. The proximate landmarks are featurized to generate a model which is used to determine a value of the advertising opportunity corresponding to a target identifier.

A system that handles delivery of a service through a client device or a secondary device paired with the client device, includes an interactive service provider and the client device. The interactive service provider inserts at least one of digital watermarks, fingerprints, and trigger identifiers at event opportunities in media content. The client device detects at least one of the inserted digital watermarks, the digital fingerprints, and the inserted trigger identifiers in the media content. The client device further renders overlay graphics on the media content and activates at least one of input devices in vicinity of the client device or the rendered overlay graphics. The client device receives trigger responses over an activated overlay graphic, via the activated input devices. The client device further displays an interactive view on the client device, to enable delivery of services in response to the received trigger responses.

An ad collision machine can be configured to evaluate collision queries for possible ad collisions and is associated with an ad datacenter configured to evaluate and respond to bid requests on behalf of a plurality of advertisers. The ad collision machine can comprise a plurality of nodes and a data cache containing a plurality of user ID—campaign ID keys representing recently submitted bids in response to bid requests. Once a selected node receives a collision query, a user ID—campaign ID key is retrieved from the collision query. If the first key is not found in the data cache, it is written to the data cache by the node and the ad collision machine returns that user ID—campaign ID pair as available to be bid on.

A method, apparatus, and computer program product are disclosed to improve generation of electronic communications. The method may provide a plurality of content slots each configured to receive content, the content comprising at least one of promotion content or non-promotion content. The method may also include maintaining a database comprising a plurality of promotion content generators and non-promotion content generators, and determining, using a processor, one of the plurality of promotion content generators or non-promotion content generators for respectively supplying corresponding promotion content or non-promotion content to each of the plurality of content slots. The determining the one of the plurality of promotion content generators or non-promotion content generators may include determining selection parameters, and scoring the plurality of promotion content generators and non-promotion content generators based at least in part on the selection parameters.

The present disclosure includes systems, methods, and non-transitory computer readable media that train and utilize multi-phase learning models to predict performance during digital content campaigns and provide digital content to client devices in a real-time bidding environment. In particular, one or more embodiments leverage organizational structure of digital content campaigns to train two learning models, utilizing different data sources, to predict performance, generate bid responses, and provide digital content to client devices. For example, the disclosed systems can train a first performance learning model in an offline mode utilizing parent-level historical data. Then, in an online mode, the disclosed systems can train a second performance learning model utilizing child-level historical data and utilize the first performance learning model and the second performance learning model to generate bid responses and bid amounts in a real-time bidding environment.

Systems, methods, and computer-readable media are disclosed for augmenting real-time bidding data with proprietary data. One method includes: receiving, at a server over an electronic communications network from a real-time impression bidder, a bid request or a request to augment a bid request with proprietary data; accessing, by the server from an internal database, proprietary data of a data augmenting service based on a user identifier of the bid request; determining, by the server, proprietary data to include in an augmented bid request based on at least one of the received bid request and the user identifier; formatting, by the server, the augmented bid request into a standardized, augmented bid request; and transmitting, by the server over the electronic communications network, the standardized, augmented bid request to the real-time impression bidder.

A digital advertising system includes at least one processor configured to execute a plurality of functional modules including an analytics module to receive and analyze client attributes associated with a website visitor and a requested website to define an analytics event. The analytics module ingests and enriches data within the analytics event and provides it to a machine learning module that generates prediction models for potential bids. A management platform receives the bidding prediction and generates candidate configs. An optimization module receives the candidate configs and applies weights and additional features to select a config and generate an optimized script for the selected config. A deployment module receives the optimized script and delivers the script to the website visitor.