Hierarchical Probabilistic Relational Models for Collaborative Filtering
نویسندگان
چکیده
This paper applies Probabilistic Relational Models (PRMs) to the Collaborative Filtering task, focussing on the EachMovie data set. We first learn a standard PRM, and show that its performance is competitive with the best known techniques. We then define a hierarchical PRM, which extends standard PRMs by dynamically refining classes into hierarchies, which improves the expressiveness as well as the context sensitivity of the PRM. Finally, we show that hierarchical PRMs achieve state-of-the-art results on this dataset.
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