Abstract: According to one aspect of the present disclosure, a computer-implemented method is provided. The method includes obtaining a plurality of user-feature embeddings for a plurality of users. The method includes generating a respective user embedding for each of the plurality of users. The method includes organizing the plurality of users into a plurality of clusters based on user embeddings. The method includes identifying particular clusters based on a respective distance between the plurality of clusters and a particular user embedding of a user. The method may include calculating a respective term-frequency (TF)-inverse document frequency (IDF) (TF-IDF) metric for each content item interacted with by at least one user of that cluster. The method may include assigning a respective rank to the plurality of content items based on the respective TF-IDF metric. The method may include providing one or more of the plurality of candidate content items to a client device.