Overlapping Community Detection in Multi-view Brain Network

Community detection in multi-view brain network is a significant research topic. Many efforts have been made on developing multi-view network community detection approaches. However, most of them can only reveal non-overlapping community structure, and the task of discovering overlapping community structure in multi-view brain network remains largely unsolved. In this paper, we propose a novel approach for Overlapping Community Detection in Multi-view Brain Network (oComm). The main idea is to design a network generative model and a node-wise cross-view consistency model for respectively measuring the within-view community quality and characterizing the cross-view community consistency. Some experiments have been conducted to confirm the effectiveness of the proposed method.