模态模块化优化中的高阶模糊成员关系

IF 10.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jing Xiao;Ya-Wei Wei;Jing Cao;Xiao-Ke Xu
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引用次数: 0

摘要

高阶社区检测(HCD)揭示了现实世界网络的中尺度结构和功能特征。虽然从不同的角度开发了许多方法,但据我们所知,没有一种方法可以提供细粒度的高阶模糊社区信息。本研究引入了一种新颖的高阶模糊隶属度概念,将基元的隶属度量化为清晰的高阶社区,从而揭示部分社区隶属关系。此外,我们利用高阶模糊隶属度,通过一个称为模糊隶属度辅助的基于基序的进化模块化的一般框架来增强HCD。一方面,设计了一种基于模糊隶属度的邻居社区修改策略来纠正错配的桥接节点,从而提高分区质量;另一方面,提出了一种基于模糊隶属度的局部社区合并策略,对过于分散的社区进行合并,增强了局部搜索能力。实验结果表明,所提出的框架在合成数据集和现实世界数据集中都优于最先进的方法,特别是在具有模糊和复杂结构的网络中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Higher Order Fuzzy Membership in Motif Modularity Optimization
Higher order community detection (HCD) reveals both mesoscale structures and functional characteristics of real-world networks. Although many methods have been developed from diverse perspectives, to our knowledge, none can provide fine-grained higher order fuzzy community information. This study introduces a novel concept of higher order fuzzy memberships that quantify the membership grades of motifs to crisp higher order communities, thereby revealing partial community affiliations. Furthermore, we utilize higher order fuzzy memberships to enhance HCD via a general framework called fuzzy memberships-assisted motif-based evolutionary modularity. On the one hand, a fuzzy membership-based neighbor community modification strategy is designed to correct misassigned bridge nodes, thereby improving partition quality. On the other hand, a fuzzy membership-based local community merging strategy is proposed to combine excessively fragmented communities, enhancing local search ability. Experimental results indicate that the proposed framework outperforms state-of-the-art methods in both synthetic and real-world datasets, particularly in networks with ambiguous and complex structures.
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来源期刊
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems 工程技术-工程:电子与电气
CiteScore
20.50
自引率
13.40%
发文量
517
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Fuzzy Systems is a scholarly journal that focuses on the theory, design, and application of fuzzy systems. It aims to publish high-quality technical papers that contribute significant technical knowledge and exploratory developments in the field of fuzzy systems. The journal particularly emphasizes engineering systems and scientific applications. In addition to research articles, the Transactions also includes a letters section featuring current information, comments, and rebuttals related to published papers.
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