Methods and systems for generating and presenting content recommendations for new users

A system comprising:

• processing circuitry configured to:
• identify, for each user of a plurality of users, a respective history comprising a set of content interactions;
• identify a reference group of users of the plurality of users, wherein the identifying the reference group is based at least in part on the respective history comprising the set of content interactions of each user of the reference group exceeding a predetermined interaction threshold;
• determine, using a machine learning model, a plurality of clusters of user preference indication data, wherein the determining is based at least in part on the respective histories comprising the set of content interactions, wherein the respective histories comprising the set of content interactions of the reference group are excluded from the determining of the plurality of clusters;
• validate a target cluster of the plurality of clusters based at least in part on the respective histories comprising the set of content interactions of the reference group;
• and
• correlate a first user to the validated target cluster based at least in part on one or more content interactions of the first user;
• and
• communication circuitry configured to:
• generate for display, for the first user, content item recommendations based at least in part on the validated target cluster.