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You are what you consume
2013
Proceedings of the 7th ACM conference on Recommender systems - RecSys '13
In this paper, we propose a novel Bayesian approach for personalized recommendations. In our approach, we model both user preferences and items under recommendation as multivariate Gaussian distributions; and make use of Normal-Inverse Wishart priors to model the recommendation agent beliefs about user types. We employ a lightweight agent-user interaction process, during which the user is presented with and asked to rate a small number of items. We then interpret these ratings in an innovative
doi:10.1145/2507157.2507158
dblp:conf/recsys/BabasCT13
fatcat:vujz46f5qvcwdo3rfwkp3gwika