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Distributed user profiling via spectral methods
2010
Performance Evaluation Review
User profiling is a useful primitive for constructing personalised services, such as content recommendation. In the present paper we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local information exchanges between users. We compute a profile vector for each user (i.e., a lowdimensional vector that characterises her taste) via spectral transformation of observed user-produced ratings for items. Our two main contributions follow: (i)
doi:10.1145/1811099.1811098
fatcat:xstbwd3rzba55f7iebtgbpkqie