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Paper proposes a new method for time-sensitive recommendations based on user activities. It is different from existing methods because it address the problem of time-varying user preferences. The paper also addresses prediction of the next returning time of a user. Learning is performed using an efficient optimization algorithm proposed by authors. Experimental section shows results on one synthetic data set in order to show that learning is efficient on large scale data and on two real data sets of modest size.