Massimo Guarascio

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—This paper presents a probabilistic co-clustering approach to pattern discovery in preference data. We extended the original formulation of the block mixture model to handle rating data; the resulting model allows the simultaneous clustering of users and items in homogeneous user communities and item categories. The parameter of the model are determined(More)
A new technique, SNIPER, is proposed for learning a model that deals with continuous values of exceptionality. Specifically, given some training objects associated with a continuous attribute <i>F</i>, SNIPER induces a rule-based model for the identification of those objects likely to score the maximum values for <i>F</i>. The purpose of SNIPER differs from(More)