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Nowadays, recommender systems face the problem of time heterogeneous feedback recommendation, in which items are recommended according to several kinds of user feedback with time stamps. Previously proposed recurrent neural network based recommendation method (RNNRec) cannot analyze feedback sequences on multiple time scales, and gradient vanishing may occur when the model is trained through back...
Widely existing conditional preference is seldom taken into consideration in recommender systems. This may lead to unsatisfying recommendation results. To address this issue, in this paper, we propose to use boosted regression trees to represent conditional preference in recommendation systems, which is more expressive than linear and quadratic function for conditional preference. Compared with the...
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