Evaluating personalized recommendation models
Abstract:
A personalized recommendation model scores each object in an interaction set of objects with which a user interacted and in a ransom set of objects with which the user lacks known interaction. A system sorts each scored object based on a decreasing order of each corresponding score, and identifies a high scoring set of the sorted objects with a number (equal to the number of objects in the interaction set of objects) of highest corresponding scores. The system aggregates a corresponding order value for each object in the high scoring set that is also in the interaction set of objects (the corresponding order value for an object is based on a corresponding order for the object in the high scoring set). The system evaluates the model for the user by dividing the aggregated order value by an aggregation of a corresponding order value for each object in the high scoring set.
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