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Recommender systems leverage product and community information to target products to consumers. Researchers have developed collaborative recommenders, content-based recommenders, and (largely ad-hoc) hybrid systems. We propose a unified probabilistic framework for merging collaborative and content-based recommendations. We extend Hofmann's  aspect model to incorporate three-way co-occurrence data among users, items, and item content. The relative influence of collaboration data versusarXiv:1301.2303v1 fatcat:rrjeeumykfhcfbzh2y7kye3nte