The recommendation algorithm based on bipartite network is superior to traditional methods on accuracy and diversity, which\nproves that considering the network topology of recommendation systems could help us to improve recommendation results.\nHowever, existing algorithms mainly focus on the overall topology structure and those local characteristics could also play an\nimportant role in collaborative recommend processing. Therefore, on account of data characteristics and application requirements\nof collaborative recommend systems, we proposed a link community partitioning algorithm based on the label propagation and\na collaborative recommendation algorithm based on the bipartite community.Then we designed numerical experiments to verify\nthe algorithm validity under benchmark and real database.
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