1. A method comprising: in a data processing system configured to generate personalized rankings of input media content items in a catalog: determining a plurality of user consumption values, wherein each of the user consumption values is associated with a user consumption data point, and wherein each user consumption data point is associated with a corresponding user and a corresponding media content item; wherein each of the user consumption values indicate a user consumption value with respect to a user that corresponds to the user consumption data point associated with the user consumption value; and a media content item that corresponds to the data point associated with the user consumption value; determining feature values for each of the user consumption data points associated with the plurality of user consumption values, wherein the feature values include a particular feature value for a particular user consumption data point indicating novelty information for a particular media content item associated with the particular user consumption data point with respect to a particular user associated with the particular user consumption data point; determining, based on the plurality of user consumption values and the feature values, predicted selection scores for an input user and the input media content items; ranking the media content items in the catalog for the input user based on the predicted selection scores; wherein the method is performed using one or more processors.