Meta Platforms, Inc.
User clustering in a latent space for identifying user interest in a content item

Abstract:

An online system targets users with a candidate content item. The online system generates a user embedding for each of a plurality of users by identifying content items interacted with by the user, identifying one or more keywords within the content items, identifying word embeddings for each of the identified keywords, and generating the user embedding with the word embeddings. The online system clusters the user embeddings while generating a cluster embedding for each cluster. The online system generates a targeting embedding for the candidate content item. Then the online system generates a score for each cluster based on a comparison of the targeting embedding with each cluster embedding. From the generated scores, the online system ranks and selects some clusters for presentation of the candidate content item.