I'd assume they'll use something like https://blog.roboflow.com/rf-detr-segmentation-preview/ and then use the "classes" as embeddings for your profile to do a similiarity match.

Or the standard given a bunch of tags (from the instance segmentation) and find your ranked list of preferences. https://librecommender.readthedocs.io/en/latest/ has a list of 5-10 standard recommender algorithms.

Or use autogluon https://auto.gluon.ai/stable/tutorials/tabular/tabular-multi... where they take Meta's large repository of annotated-images (DINOv2) and use them to classify then do the recommendation system on tabular (database tables).

This stuff has been standard for years now.