Real-time content integration based on machine learned selections

A system comprising:

• one or more processors of a machine;
• and
• a memory storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising:
• identifying training data that includes historical user data and historical content data, at least some of the training data being related to content items that can be selected by performing user device input actions;
• training a machine learning classifier on the training data, the machine learning classifier being trained to generate, for each of a plurality of given content items associated with a given user, a relevancy value, the relevancy value for each given content item being indicative of a likelihood that the given user will perform a first user device input action and of a likelihood that the given user will perform a second user device input action, in response to being presented with the given content item as part of a content collection displayed on a user device of the given user, and the first user device input action being different from the second user device input action;
• receiving, by the machine learning classifier, a plurality of candidate content items associated with a first user, the candidate content items having been submitted to a platform, each of the candidate content items submitted to the platform with a submitted value that is associated with a bid;
• automatically generating, by the machine learning classifier, the relevancy value for each candidate content item associated with the first user;
• and
• identifying at least one of the plurality of candidate content items for inclusion in a first content collection associated with the platform, to be displayed on a first user device of the first user based on a final value for each of the at least one identified candidate content item, the final value generated based on the submitted value and a normalized relevancy value, the normalized relevancy value being generated by normalizing the relevancy value generated by the machine learning classifier for each of the at least one identified candidate content item.

A non-transitory machine-readable storage device embodying instructions that, when executed by a machine, cause the machine to perform operations comprising:

• identifying training data that includes historical user data and historical content data, at least some of the training data being related to content items that can be selected by performing user device input actions;
• training a machine learning classifier on the training data, the machine learning classifier being trained to generate, for each of a plurality of given content items associated with a given user, a relevancy value, the relevancy value for each given content item being indicative of a likelihood that the given user will perform a first user device input action and of a likelihood that the given user will perform a second user device input action, in response to being presented with the given content item as part of a content collection displayed on a user device of the given user, and the first user device input action being different from the second user device input action;
• receiving, by the machine learning classifier, a plurality of candidate content items associated with a first user, the candidate content items having been submitted to a platform, each of the candidate content items submitted to the platform with a submitted value that is associated with a bid;
• automatically generating, by the machine learning classifier, the relevancy value for each candidate content item associated with the first user;
• and
• identifying at least one of the plurality of candidate content items for inclusion in a first content collection associated with the platform, to be displayed on a first user device of the first user based on a final value for each of the at least one identified candidate content item, the final value generated based on the submitted value and a normalized relevancy value, the normalized relevancy value being generated by normalizing the relevancy value generated by the machine learning classifier for each of the at least one identified candidate content item.