Gaussian Process Factorization Machines for Context-aware Recommendations
Context-aware recommendation (CAR) can lead to significant improvements in the relevance of the recommended items by modeling the nuanced ways in which context influences preferences. The dominant approach in context-aware recommendation has been the multidimensional latent factors approach in which users, items, and context variables are represented as latent features in a low-dimensional space. An interaction between a user, item, and a context variable is typically modeled as some linear...[Show more]
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