Huang Ling, Wang Chang-Dong, Yu Philip S
IEEE Trans Cybern. 2023 May;53(5):3060-3074. doi: 10.1109/TCYB.2021.3125227. Epub 2023 Apr 21.
Community detection in multiview networks has drawn an increasing amount of attention in recent years. Many approaches have been developed from different perspectives. Despite the success, the problem of community detection in adversarial multiview networks remains largely unsolved. An adversarial multiview network is a multiview network that suffers an adversarial attack on community detection in which the attackers may deliberately remove some critical edges so as to hide the underlying community structure, leading to the performance degeneration of the existing approaches. To address this problem, we propose a novel approach, called higher order connection enhanced multiview modularity (HCEMM). The main idea lies in enhancing the intracommunity connection of each view by means of utilizing the higher order connection structure. The first step is to discover the view-specific higher order Microcommunities (VHM-communities) from the higher order connection structure. Then, for each view of the original multiview network, additional edges are added to make the nodes in each of its VHM-communities fully connected like a clique, by which the intracommunity connection of the multiview network can be enhanced. Therefore, the proposed approach is able to discover the underlying community structure in a multiview network while recovering the missing edges. Extensive experiments conducted on 16 real-world datasets confirm the effectiveness of the proposed approach.
近年来，多视图网络中的社区检测受到了越来越多的关注。人们从不同角度开发了许多方法。尽管取得了成功，但对抗性多视图网络中的社区检测问题在很大程度上仍未得到解决。对抗性多视图网络是一种在社区检测中遭受对抗性攻击的多视图网络，攻击者可能会故意删除一些关键边，以隐藏潜在的社区结构，导致现有方法的性能退化。为了解决这个问题，我们提出了一种新颖的方法，称为高阶连接增强多视图模块度（HCEMM）。其主要思想在于通过利用高阶连接结构来增强每个视图的社区内连接。第一步是从高阶连接结构中发现特定于视图的高阶微社区（VHM-社区）。然后，对于原始多视图网络的每个视图，添加额外的边，使每个VHM-社区中的节点像团一样完全连接，从而增强多视图网络的社区内连接。因此，所提出的方法能够在恢复缺失边的同时发现多视图网络中的潜在社区结构。在16个真实世界数据集上进行的大量实验证实了所提方法的有效性。
