Efficient critical relationships identification in bipartite networks

Chen Chen, Qiuyu Zhu, Yanping Wu, Renjie Sun, Xiaoyang Wang, Xijuan Liu

Abstract: Bipartite graphs, which consist of two different types of entities, are widely used to model many real-world applications. In bipartite networks, (α,β)-core is an essential model to measure the entity engagement. In this paper, we propose and investigate the problem of (α,β)-core minimization, which aims to identify a set of b edges whose deletion can minimize the size of resulting collapsed (α,β)-core. To our best knowledge, this is the first work to investigate the (α,β)-core minimization problem in bipartite graph. We prove the problem is NP-hard and our object function is monotonic but not submodular. Then, we propose a baseline algorithm by invoking the greedy framework. To reduce the computation cost and candidate space, novel pruning techniques are devised. We further develop a group based algorithm to optimize the search. Finally, we conduct comprehensive experiments over 6 real-life bipartite networks to demonstrate the advantages of the proposed techniques.