Yong Yu1, Yongjun Luo1, Tong Li2, Shudong Li3, *, Xiaobo Wu4, Jinzhuo Liu1, *, Yu Jiang3, *
CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 489-507, 2020, DOI:10.32604/cmc.2020.07616
Abstract Personalized recommendation algorithms, which are effective means to solve information overload, are popular topics in current research. In this paper, a recommender system combining popularity and novelty (RSCPN) based on one-mode projection of weighted bipartite network is proposed. The edge between a user and item is weighted with the item’s rating, and we consider the difference in the ratings of different users for an item to obtain a reasonable method of measuring the similarity between users. RSCPN can be used in the same model for popularity and novelty recommendation by setting different parameter values and analyzing how a change in… More >
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