Community detection from fuzzy and higher-order perspectives

被引：2

作者：

Xiao, Jing ^{[1
]}

Xu, Xiao-ke ^{[2
]}

机构：

[1] Dalian Minzu Univ, Coll Informat & Commun Engn, Dalian 116600, Peoples R China

[2] Beijing Normal Univ, Sch Journalism & Commun, Beijing 100875, Peoples R China

来源：

EPL | 2023年 / 144卷 / 01期

关键词：

OVERLAPPING COMMUNITIES; SOCIAL NETWORKS; MODULARITY; ALGORITHM; OPTIMIZATION;

D O I：

10.1209/0295-5075/acfdc9

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

- Our ability to observe the mesoscale topology of complex networks through com-munity detection has significantly advanced in the past decades. This progress has opened up new frontiers in discovering more sophisticated and meaningful community structures that pos-sess fuzzy and higher-order characteristics. This review provides an overview of two emerging research directions, which are fuzzy and higher-order community detection. It includes related concepts and practical scenarios, mathematical descriptions and latest advancements, as well as current challenges and future directions. Therefore, it will facilitate researchers in swiftly grasping the two emerging fields, offering valuable insights for future development of community detection studies.

引用

页数：8

共 55 条

[1] Community detection from biological and social networks: A comparative analysis of metaheuristic algorithms [J].

Atay, Yilmaz ;

Koc, Ismail ;

Babaoglu, Ismail ;

Kodaz, Halife .

APPLIED SOFT COMPUTING, 2017, 50 :194-211

[2] A robust ant colony optimization-based algorithm for community mining in large scale oriented social graphs [J].

Ben Romdhane, L. ;

Chaabani, Y. ;

Zardi, H. .

EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (14) :5709-5718

[3] Higher-order organization of complex networks [J].

Benson, Austin R. ;

Gleich, David F. ;

Leskovec, Jure .

SCIENCE, 2016, 353 (6295) :163-166

[4] Fuzzy clustering in community detection based on nonnegative matrix factorization with two novel evaluation criteria [J].

Binesh, Neda ;

Rezghi, Mansoor .

APPLIED SOFT COMPUTING, 2018, 69 :689-703

[5] FuzAg: Fuzzy Agglomerative Community Detection by Exploring the Notion of Self-Membership [J].

Biswas, Anupam ;

Biswas, Bhaskar .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (05) :2568-2577

[6] Inference of hyperedges and overlapping communities in hypergraphs [J].

Contisciani, Martina ;

Battiston, Federico ;

De Bacco, Caterina .

NATURE COMMUNICATIONS, 2022, 13 (01)

[7] A complex network community detection algorithm based on label propagation and fuzzy C-means [J].

Deng, Zheng-Hong ;

Qiao, Hong-Hai ;

Song, Qun ;

Gao, Li .

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 519 :217-226

[8] Community detection in complex networks: From statistical foundations to data science applications [J].

Dey, Asim K. ;

Tian, Yahui ;

Gel, Yulia R. .

WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2022, 14 (02)

[9] 20 years of network community detection [J].

Fortunato, Santo ;

Newman, Mark E. J. .

NATURE PHYSICS, 2022, 18 (08) :848-850

[10] Community detection in networks: A user guide [J].

Fortunato, Santo ;

Hric, Darko .

PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 2016, 659 :1-44

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