Conjugate priors for Gaussian emission plsa recommender systems
Collaborative filtering for recommender systems seeks to learn and predict user preferences for a collection of items by identifying similarities between users on the basis of their past interest or interaction with the items in question. In this work, we present a conjugate prior regularized extension of Hofmann's Gaussian emission probabilistic latent semantic analysis model, able to overcome th
