Abstract: Systems and methods are described herein for novel uses and/or improvements for designing user-specific interfaces using machine learning models. When a request to display certain data by an application is received, an application token and a user token may be retrieved and combined into a consolidated token. The consolidated token may be input into a machine learning model to obtain a user interface token for an application. The user interface token may indicate user interface settings/configuration desired/preferred by a user. The user interface token may then be sent to the application to cause the application to display the data using user interface configurations within the user interface token.

Abstract: An exemplary method includes a media program distribution service system 1) receiving data representative of a plurality of scene tags specifying one or more media program scenes tagged by a plurality of end users of a media program distribution service, 2) aggregating the plurality of scene tags, 3) determining, based on a favorite scenes determination heuristic and the aggregate scene tags, a set of one or more favorite scenes that are most popular among the plurality of end users of the media program distribution service, and 4) providing, based on the determined set of one or more favorite scenes, a favorite scene based feature of the media program distribution service. Corresponding systems and methods are also disclosed.