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Recent decade has witnessed the increasing popularity of recommender systems, which help users acquire relevant commodities and services from overwhelming resources on Internet. Some simple physical diffusion processes have been used to design effective recommendation algorithms for user-object bipartite networks, typically mass diffusion (MD) and heat(More)
Abstract – In last decades, diversity and accuracy have been regarded as two essential measures in evaluating recommender systems. However, a clear concern is that a model focusing excessively on one measure will put the other one at risk, which means that it is not easy to greatly improve diversity and accuracy simultaneously. In this paper, we propose a(More)
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