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通过加权图社区博弈进行重叠社区检测。

Overlapping communities detection through weighted graph community games.

机构信息

Dipartimento di Sociologia e Ricerca Sociale, Università di Trento, Trento, Italy.

IMUS, Universidad de Sevilla, Sevilla, Spain.

出版信息

PLoS One. 2023 Apr 4;18(4):e0283857. doi: 10.1371/journal.pone.0283857. eCollection 2023.

Abstract

We propose a new model to detect the overlapping communities of a network that is based on cooperative games and mathematical programming. More specifically, communities are defined as stable coalitions of a weighted graph community game and they are revealed as the optimal solution of a mixed-integer linear programming problem. Exact optimal solutions are obtained for small and medium sized instances and it is shown that they provide useful information about the network structure, improving on previous contributions. Next, a heuristic algorithm is developed to solve the largest instances and used to compare two variations of the objective function.

摘要

我们提出了一种新的模型来检测网络的重叠社区,该模型基于合作博弈和数学规划。更具体地说,社区被定义为加权图社区博弈的稳定联盟,并且它们被揭示为混合整数线性规划问题的最优解。对于小和中型实例,我们获得了精确的最优解,并表明它们提供了有关网络结构的有用信息,改进了先前的贡献。接下来,开发了一种启发式算法来解决最大实例,并用于比较目标函数的两个变体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a59d/10072486/a34745c62308/pone.0283857.g001.jpg

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