Standard

Cooperative Game Theory Approaches for Network Partitioning. / Avrachenkov, Konstantin E.; Kondratev, Aleksei Yu.; Mazalov, Vladimir V.

2017. 591-602 Paper presented at 23rd International Conference on Computing and Combinatorics, COCOON 2017, Hong Kong, China.

Research output: Contribution to conference › Paper › peer-review

Harvard

Avrachenkov, KE, Kondratev, AY & Mazalov, VV 2017, 'Cooperative Game Theory Approaches for Network Partitioning', Paper presented at 23rd International Conference on Computing and Combinatorics, COCOON 2017, Hong Kong, China, 3/08/17 - 5/08/17 pp. 591-602. https://doi.org/10.1007/978-3-319-62389-4_49

APA

Avrachenkov, K. E., Kondratev, A. Y., & Mazalov, V. V. (2017). Cooperative Game Theory Approaches for Network Partitioning. 591-602. Paper presented at 23rd International Conference on Computing and Combinatorics, COCOON 2017, Hong Kong, China. https://doi.org/10.1007/978-3-319-62389-4_49

Vancouver

Avrachenkov KE, Kondratev AY, Mazalov VV. Cooperative Game Theory Approaches for Network Partitioning. 2017. Paper presented at 23rd International Conference on Computing and Combinatorics, COCOON 2017, Hong Kong, China. https://doi.org/10.1007/978-3-319-62389-4_49

Author

Avrachenkov, Konstantin E. ; Kondratev, Aleksei Yu. ; Mazalov, Vladimir V. / Cooperative Game Theory Approaches for Network Partitioning. Paper presented at 23rd International Conference on Computing and Combinatorics, COCOON 2017, Hong Kong, China.12 p.

BibTeX

@conference{723cc93586784111b91fc0558439e956,
title = "Cooperative Game Theory Approaches for Network Partitioning",
abstract = "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.",
author = "Avrachenkov, {Konstantin E.} and Kondratev, {Aleksei Yu.} and Mazalov, {Vladimir V.}",
year = "2017",
doi = "10.1007/978-3-319-62389-4_49",
language = "русский",
pages = "591--602",
note = "null ; Conference date: 03-08-2017 Through 05-08-2017",

}

RIS

TY - CONF

T1 - Cooperative Game Theory Approaches for Network Partitioning

AU - Avrachenkov, Konstantin E.

AU - Kondratev, Aleksei Yu.

AU - Mazalov, Vladimir V.

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

U2 - 10.1007/978-3-319-62389-4_49

DO - 10.1007/978-3-319-62389-4_49

M3 - материалы

SP - 591

EP - 602

Y2 - 3 August 2017 through 5 August 2017

ER -

ID: 132702056