In this paper, we focus on the problem of context-aware recommendation using tensor factorization. Tra- ditional tensor-based models in context-aware recommendation scenario only consider user-item-context interactions. In this paper, we argue that rating can’t be totally explained by the interactions and the rat- ing also influenced by the combined impact of overall mean, user bias, item bias and context bias. Based on this hypothesis, we propose a novel context-aware recommendation model named
