Recommendation can be seen as tantamount to blind sentiment analysis, i.e. a sentiment prediction without text data. In that sense, we aim at encoding priors on users and items while reading their reviews, using a deep architecture with personalized attention modeling. Following this idea, we build an hybrid hierarchical sentiment classifier which is then used as a recommender system in inference.