title: A collaborative recommend algorithm based on bipartite community.
abstract: The recommendation algorithm based on bipartite network is superior to traditional methods on accuracy and diversity, which proves that considering the network topology of recommendation systems could help us to improve recommendation results. However, existing algorithms mainly focus on the overall topology structure and those local characteristics could also play an important role in collaborative recommend processing. Therefore, on account of data characteristics and application requirements of collaborative recommend systems, we proposed a link community partitioning algorithm based on the label propagation and a collaborative recommendation algorithm based on the bipartite community. Then we designed numerical experiments to verify the algorithm validity under benchmark and real database.
authors: Suzhou Industrial Park Institute of Services Outsourcing, Suzhou, Jiangsu 215123, China ; School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China.
authors: Yuchen
authors: Y
authors: Fu
authors: School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China.
authors: Quan
authors: Q
authors: Liu
authors: School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China.
authors: Zhiming
authors: Z
authors: Cui
mesh_terms: D000465:Algorithms; D003299:Cooperative Behavior