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Given a set of pairwise comparisons, the classical ranking problem computes a single ranking that best represents the preferences of all users. In this paper, we study the problem of inferring individual preferences, arising in the context of making personalized recommendations. In particular, we assume that there are n users of r types; users of the same type provide similar pairwise comparisons for m items according to the Bradley-Terry model. We propose an efficient algorithm that accuratelyarXiv:1502.04631v2 fatcat:gl23lvhyybbyngqk5ssma6myhi