Detecting communities in higher-order networks by using their derivative graphs

被引:5
|
作者
Contreras-Aso, Gonzalo [1 ,4 ,5 ]
Criado, Regino [1 ,2 ,3 ,4 ]
de Salas, Guillermo Vera [1 ,4 ]
Yang, Jinling [1 ]
机构
[1] Univ Rey Juan Carlos, Dept Matemat Aplicada Ciencia Ingn Mat & Tecnol El, C Tulipan S-N, Madrid 28933, Spain
[2] Univ Rey Juan Carlos, Data Complex Networks Cybersecur Sci Technol Inst, Plaza Manuel Becerra 14, Madrid 28028, Spain
[3] Univ Rey Juan Carlos, Lab Math Computat Complex Networks & Their Applica, C Tulipan S-N, Madrid 28933, Spain
[4] Northwestern Polytech Univ, Unmanned Syst Res Inst, Xian 710072, Shaanxi, Peoples R China
[5] Univ Rey Juan Carlos, Calle Tulipan S-N, Madrid 28933, Spain
关键词
Hypergraph; Derivative of a hypergraph; Higher-order network; Community; Communities in a hypergraph; UPGMA; Hierarchical clustering; COMPLEX NETWORKS; WORLD;
D O I
10.1016/j.chaos.2023.114200
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Similar to what happens in the pairwise network domain, the communities of nodes of a hypergraph (also called higher-order network) are formed by groups of nodes that share many hyperedges, so that the number of hyperedges they share with the rest of the nodes is significantly smaller, and therefore these communities can be considered as independent compartments (or super-clusters) of the hypergraph. In this work we present a method, based on the so-called derivative graph of a hypergraph, which allows the detection of communities of a higher-order network without high computational cost and several simulations are presented that show the significant computational advantages of the proposed method over other existing methods.
引用
收藏
页数:8
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