网络划分的合作博弈方法
Cooperative Game Theory Approaches for Network Partitioning
摘要：
本文主要研究网络中社区发现的博弈论方法。传统的社团结构检测方法是基于网络内部稠密子图的选择。在这里，我们建议使用合作博弈论的方法，不仅突出的链接密度，但也集群形成的机制。具体来说，我们建议两种方法从合作博弈论：第一种方法是基于迈尔森值，而第二种方法是基于享乐游戏。这两种方法都允许检测具有不同分辨率的聚类。然而，在享乐博弈方法中，分辨率参数的调整特别直观。此外，基于模块的方法及其推广可以被视为享乐游戏的特殊情况。
英文摘要：
The paper is devoted to game-theoretic methods for community detection in networks. The traditional methods for detecting community structure are based on selecting denser subgraphs inside the network. Here we propose to use the methods of cooperative game theory that highlight not only the link density but also the mechanisms of cluster formation. Specifically, we suggest two approaches from cooperative game theory: the first approach is based on the Myerson value, whereas the second approach is based on hedonic games. Both approaches allow to detect clusters with various resolution. However, the tuning of the resolution parameter in the hedonic games approach is particularly intuitive. Furthermore, the modularity based approach and its generalizations can be viewed as particular cases of the hedonic games.
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