An electronic device comprising a display; a memory to store recommended content information and a processor which: controls a communication interface to communicate with an external device that receives content from a plurality of content providers and provides the content to the electronic device; when a user command to display a UI screen including information on the external device is input, obtains recommended content information related to the plurality of content providers connected to the external device on the basis of information stored in the memory; and controls the display to display a UI screen to which the external device and the obtained recommended content information are mapped, where the information stored in the memory is obtained on the basis of viewing history information corresponding to the external device.

Some implementations relate to methods, systems, and computer-readable media for digital advertising within a first virtual experience provided at a virtual experience platform. A virtual user engagement portal is provided within the first virtual experience that includes a portal member configured to transport an avatar to a second virtual experience. The second virtual experience may be associated with at least one media item, and may include a plurality of virtual items, activities, and other virtual content associated with the at least one media item. A return portal may be provided within the second virtual experience to return an avatar to the first virtual experience. User engagement metrics and/or advertising metrics may be aggregated and/or computed based on avatar interactions within the second virtual experience.

A computer server includes processor and memory hardware. The processor hardware executes instructions including parsing a hypertext transfer protocol (HTTP) request from a first user agent to identify a first data object matching a set of characteristics and generating a new data element based on the HTTP request. The instructions include, in response to the first data object being present: extracting a first set of serialized data elements and serializing them with the new data element to generate a second data object. The instructions include, in response to the first data object being absent and a user associated with the first user agent being identifiable: determining a second set of serialized data elements based on an identity of the user, and serializing them with the new data element to generate the second data object. The instructions include transmitting an HTTP response including the second data object.

A method includes causing a computer of a communication terminal to perform a process including acquiring, in response to receipt of a beacon signal from a vending machine, identification information of the vending machine and type information of drinks in the vending machine from the vending machine; transmitting a user ID of a user of the communication terminal to a first server that securely manages personal information including preference information on drinks of the user; acquiring from the first server, the preference information of the user corresponding to the user ID; acquiring weather information of a current location of the communication terminal; generating, based on the acquired pieces of information, a push notification screen that recommends at least one drink that matches a preference of the user indicated by the preference information in relation to weather indicated by the weather information; and displaying the push notification screen.

The subject matter of this specification can be embodied in, among other things, a method that receives at a server a first request to rebroadcast a first sponsored content item that was displayed on the social network to the first user to a second user. A second request to display at least one sponsored content item to the second user when the second user accesses an electronic document associated with the social network is received at the server. The first sponsored content item is retrieved for rebroadcast from one or more sponsored content items indicated for rebroadcast to the second user. The first sponsored content item is output to the second user of the social network in response to the second request to display and without requiring the second user to select the first sponsored content item for display.

An online system receives offline conversion data in real-time from a third party system regarding an offline user, the offline conversion data indicating an action performed by the offline user and identifying information for the offline user. The online system identifies a local user matching the offline user based on the identifying information for the offline user. The online system stores the offline conversion for the identified local user. The online system determines an attribution to a sponsored content item for the offline conversion. The online system presents updated information regarding the offline conversion to the third party system in real-time.

A computing device for analyzing data from user spending patterns to determine offers to be presented to credit card customers comprises a processing element configured to: receive transaction data for a plurality of transactions for each of a plurality of credit card numbers; input the transaction data into an encoder that performs linear transformations and nonlinear transformations to produce latent space data with each latent space data point being associated with one credit card number; input the latent space data into a clustering element which associates each credit card number with one of a plurality of clusters; and make an upgrade offer to credit card numbers that have a normal credit status and which are associated with clusters that include credit card numbers that have a preferred credit status.

A method for targeting advertising includes receiving, at a first server, customer action information associated with the customer, and receiving a plurality of advertising campaigns. The method also includes generating, using a first algorithm, a list of products derived from the customer action information that the customer may have interest in over a first time period, and generating, using a second algorithm, a ranked list of product categories derived from the customer action information that, if purchased by the customer, would generate a highest amount of revenue over a second time period. The method further includes sending a first communication associated with a first advertising campaign of the plurality of advertising campaigns to a customer device, the first advertising campaign chosen by a third algorithm that incorporates, as input, the list of products and the ranked list of product categories.

A method for processing a mobile advertisement, a proxy server, and a terminal are provided. The method includes receiving, by a proxy server, an advertisement request from a proxy software development kit (SDK) embedded into an application. The advertisement request information carries an identifier of the application. The method further includes obtaining identifiers of corresponding advertisement networks and traffic allocation of the advertisement networks according to the identifier of the application. The method further includes selecting an identifier of an advertisement network according to the traffic allocation, and sending an advertisement information request to the corresponding advertisement network according to the selected identifier of the advertisement network. The method further includes receiving advertisement information from the corresponding advertisement network according to the advertisement information request, and sending the advertisement information to the proxy SDK such that the proxy SDK displays the advertisement information in an advertisement position of the application.

An information distribution server includes a status estimation unit that derives an expected value of the number of distributions of content in each status in each time period, a score derivation unit that derives a probability score of the content for each time period and for each status, a distribution target determination unit that extracts a combination of a time period, status, and content in which the probability score is equal to or higher than a predetermined threshold value, and determines content relevant to the combination as a distribution target, and a distribution unit that distributes the distribution target on the basis of information indicated by the combination extracted by the distribution target determination unit.