Abstract: Provided is a system and method for digital content generation and recommendation. A first plurality of stories are collected from various content sources over a network. A second plurality of stories are selected from the first plurality of stories such that a degree of similarity between any two stories of the second plurality of stories is below a determined threshold. A summary and a headline are generated for a first story of the second plurality of stories. A set of images are selected, from an image database, for the first story based on the generated summary and headline. A multimedia item including the summary, the headline, and a first image of the set of images is created. The multimedia item is presented on a lock screen interface of a user device, displaying the generated summary, the generated headline, and the first image on the lock screen interface.

Abstract: Example implementations relate to expected selected impression determinations using frequency cap parameters. In an example, a likelihood request for display of digital content is received. The likelihood request includes at least one constraint parameter and at least one frequency cap parameter. A first quantity of impressions per user is obtained based on the at least one constraint parameter and a suppression ratio for the at least one frequency cap parameter is determined. The suppression ratio is a ratio of a selection likelihood under the at least one constraint parameter and the frequency cap parameter to a selection likelihood under the at least one constraint parameter. One or more of the first quantity of impressions per user is suppressed based on the suppression ratio to generate a second quantity of impressions per user and the at least one constraint parameter is adjusted based on the second quantity of impressions per user.

Abstract: Provided is a system and method for digital content generation and recommendation. A first plurality of stories are collected from various content sources over a network. A second plurality of stories are selected from the first plurality of stories such that a degree of similarity between any two stories of the second plurality of stories is below a determined threshold. A summary and a headline are generated for a first story of the second plurality of stories. A set of images are selected, from an image database, for the first story based on the generated summary and headline. A multimedia item including the summary, the headline, and a first image of the set of images is created. The multimedia item is presented on a lock screen interface of a user device, displaying the generated summary, the generated headline, and the first image on the lock screen interface.

Abstract: Example implementations related to automated generation of images is disclosed. In an example, a request to generate an interface element package for a selected item is received and, in response to receiving the request, a foreground image element and a contextually appropriate background image are generated. An integrated image is generated by integrating the foreground image element into the contextually appropriate background image at a contextually appropriate position. The foreground image element is unmodified in the integrated image. At least one textual interface element is generated. The interface element package includes at least the integrated image and the textual interface element.

Abstract: Systems and methods for forecasting unique user counts for advertising campaigns are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, a user forecast request; determining, based on the user forecast request, campaign data associated with an advertising campaign; computing, based on at least one model and the campaign data, a total number of unique users forecasted to be reached by the advertising campaign in a future time period; generating forecasted user data based on the number of unique users; and transmitting, in response to the user forecast request, the forecasted user data to the computing device.

Abstract: Systems and methods for predicting advertising related inventory and opportunity for advertising campaigns based on metadata and dimensionality reduction are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, a prediction request associated with an advertising campaign; determining a metadata set associated with the advertising campaign; generating, based on a machine learning model, an embedding for the metadata set; determining, based on the embedding, at least one embedding associated with at least one advertising opportunity data; generating predicted advertising opportunity data for the advertising campaign based on the at least one advertising opportunity data; and transmitting the predicted advertising opportunity data to the computing device.

Abstract: Provided is a system and method for digital content generation and recommendation. A first plurality of stories are collected from various content sources over a network. A second plurality of stories are selected from the first plurality of stories such that a degree of similarity between any two stories of the second plurality of stories is below a determined threshold. A summary and a headline are generated for a first story of the second plurality of stories. A set of images are selected, from an image database, for the first story based on the generated summary and headline. A multimedia item including the summary, the headline, and a first image of the set of images is created. The multimedia item is presented on a lock screen interface of a user device, displaying the generated summary, the generated headline, and the first image on the lock screen interface.

Abstract: A method for controlling access to enterprise objects for an external user. The method includes receiving a search request from an external SRM for access to an enterprise object in an enterprise system, evaluating an enterprise rule tree to determine access and editing privileges granted to an external user accessor for the enterprise object, granting the access and editing privileges to the external user accessor based upon the enterprise rule tree, and sending the enterprise object as external user data to the SRM when the enterprise rule tree authenticates the external user accessor.