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A Bayesian hierarchical model is applied to the contextaware collaborative recommendation problem. The proposed method treats users, items, and contexts symmetrically, in contrast to existing contextaware extensions of collaborative filters, which treat them asymmetrically. Evaluation using internet questionnaire data demonstrates that the proposed method outperforms conventional collaborative filtering (CF) models and is very stable, even when the number of ratings is very small.