Abstract：To reveal the hidden relationship between complex network structures and recommend items to users more accurately, an algorithmbased on joint nonnegative matrix factorization (JNMF) is proposed. In the algorithm, user-based collaborative filtering is combined with item-based collaborative filtering. The validity and the convergence of the algorithm are presented in the appendix as well. The experimental results show that the proposed algorithm can combine user-based collaborative filtering algorithm and item-based collaborative filtering algorithm effectively, reduce the mean absolute error to some extent and improve the accuracy of recommendation.
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2016, Vol. 29 
