将接近度量扩展到属性网络用于社区检测

IF 0.7 4区数学 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Advances in Complex Systems Pub Date : 2021-12-15 DOI:10.25088/complexsystems.30.4.441

Rinat Aynulin, P. Chebotarev

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引用次数: 0

摘要

图上的接近度量被广泛用于解决网络分析中的各种问题，包括社区检测。以往的研究主要考虑了无属性网络的接近度量。然而，属性信息，特别是节点属性，允许对网络结构进行更深入的探索。本文将一些接近测度的定义推广到有属性网络的情况。为了考虑节点属性，属性相似度被嵌入到邻接矩阵中。在现实网络社区检测的背景下，对得到的属性感知接近度量进行了数值研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Extending Proximity Measures to Attributed Networks for Community Detection

Proximity measures on graphs are extensively used for solving various problems in network analysis, including community detection. Previous studies have considered proximity measures mainly for networks without attributes. However, attribute information, node attributes in particular, allows a more in-depth exploration of the network structure. This paper extends the definition of a number of proximity measures to the case of attributed networks. To take node attributes into account, attribute similarity is embedded into the adjacency matrix. Obtained attribute-aware proximity measures are numerically studied in the context of community detection in real-world networks.

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来源期刊

Advances in Complex Systems 综合性期刊-数学跨学科应用

CiteScore

1.40

自引率

0.00%

发文量

121

审稿时长

6-12 weeks

期刊介绍： Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.