An online system may identify content with which a user has an interest. For example, the online system may determine that a user has an interest in the content based on interaction information indicating that the user interacted with the content. In a particular example, the online system may identify image concepts included in the content based on computer vision techniques that recognize the image concepts. The online system may model probabilities that image concepts will appeal to users. Based on the modeled probabilities, the online system may automatically recommend image concepts for inclusion in candidate images, automatically generate candidate images, or assess candidate images to determine a probability of user interaction with the assessed candidate images.

A retail ticking system including a processing unit, a web services server for receiving sent messages from a terminal client device and delivering presentation data to the terminal, a credential server for receiving and verifying a processed credential access request, a profile management server for storing and retrieving user information, and a message broker adapted to receive and manage event messages.

A performance internet marketing self-optimizing, anthropomorphic, artificial intelligence-based system and method to quote, compare and purchase benefits products from a benefits provider. The system and method collects information from an online advertising platform during the process and returns the collected information to the online advertising platform for optimization of the online advertising platform.

Embodiments provide computer systems, computer-executable methods and one or more non-transitory computer-readable media for offering one or more promotions to consumers using a promotion and marketing service. User input may be received from a first consumer interface associated with a first consumer, the user input including an interest indication relating to a first promotion. An association between the first consumer and a second consumer for sharing of promotions may be programmatically retrieved or generated. Based on the association, it may be determined whether to offer the first promotion to the second consumer based on one or more characteristics associated with the second consumer. Based on a determination that the first promotion should be offered to the second consumer, an indication may be outputted, the indication configured to cause an impression of the first promotion to be generated on a second consumer interface associated with the second consumer.

A mobile terminal includes a touch screen display, a camera, a power button and an activation button for turning on the touch screen display. The mobile terminal has a first function and a second function to perform in response to user input and provides user settings for configuring at least one of the first and second functions such that the at least one of the first and second functions is performed along with turning on the touch screen display when pressing of the activation button is detected while the touch screen display is turned off. The mobile terminal is configured to perform the first and second functions depending upon length of pressing of the activation button in addition to turning on the touch screen display.

A system includes a first computing device client associated with a first user in a community of users operable to send content to publish to a data aggregation server. The data aggregation server is operable to receive the content to publish from the first computing device client, host a first user profile associated with the first user of the first computing device client, the first user profile identifying a targeted recipient in the community of users, and disseminate automatically the content received from the first computing device client to a second computing device client associated with the targeted recipient, without receiving input from the first computing device client explicitly specifying the targeted recipient to whom the content is disseminated.

Methods, computer-readable media, systems, and/or apparatuses for providing offer and insight generation functions are provided. For instance, user input may be received requesting generation of an offer. In response to receiving the request, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the application may be executed by the device and may facilitate establishing a communication session with a third party system, identifying and extracting data from the third party system, and transmitting the extracted data to an entity for evaluation. In some examples, evaluation by the entity may include generating one or more insights, outputs and the like. In some arrangements, the evaluation may be performed using machine learning and, in some examples, may be performed in real-time or near real-time.

Methods, systems, and devices for providing in-flight communication sessions. In some examples, a communication session delivery system may provide network access service or other types of content once a passenger has completed a brand interaction. The brand interaction may be any number of options that a brand partner may require in exchange for access to content. The communication session delivery system may choose from a plurality of reward offers and then display the chosen offers to a passenger. The chosen offers may be selected based on profile information of a passenger and characteristics targeted by a brand partner. The passenger may then choose an offer and perform the required brand interaction. Once the brand interaction has been verified, the passenger may receive the reward associated with the offer.

Methods and apparatus are described for producing a computer-generated image by monitoring one or more kinds of activity of a user to identify at least one item of interest; and creating a computer-generated image including a representation of the item of interest overlaid onto an image of a model, environment or contextually relevant scenario. The process begins at 102 with monitoring a user's online activity. Software tracks and stores which purchasable items on the website/mobile application the user appears to be most interested. In a particular example, a user's abandoned basket feed is tracked and stored. In another example, cookies information is stored. Another indicator of items that a user is most interested in is length of time browsing a webpage associated with a particular item. Dwell time and cursor tracking software may also be used to identify which items the user viewed most. At 114, a model simulation is created. The object to be modelled relates to the items of interest. In the example where the items of interest are wearable items such as clothing garments, the model to be simulated is a human person said human person resembling the user as closely as possible based on the available personal data.

Described are platforms, systems, and methods for providing targeted content based on a determined persona. In one aspect, a method comprises receiving, from a user-interface, user-generated data comprising readiness, values, or personality, of a user; processing the user-generated data through a persona clustering model to determine a persona from a plurality of personas for the user, the persona clustering model trained with previously received user-generated data for a plurality of other users; determining targeted content for the user based on the persona; and providing, to the user-interface, the targeted content customized for the user.