对抗制
计算机科学
模块化(生物学)
连接(主束)
集团
群落结构
人工智能
订单(交换)
数据挖掘
数学
几何学
财务
遗传学
生物
组合数学
经济
作者
Ling Huang,Chang‐Dong Wang,Philip S. Yu
出处
期刊:IEEE transactions on cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2023-05-01
卷期号:53 (5): 3060-3074
被引量:14
标识
DOI:10.1109/tcyb.2021.3125227
摘要
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.
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