Network partitioning algorithms as cooperative games

The paper is devoted to game-theoretic methods for community detection in networks. The traditional methods for detecting community structure are based on selecting dense subgraphs inside the network. Here we propose to use the methods of cooperative game theory that highlight not only the link dens...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Computational social networks Jg. 5; H. 1; S. 11 - 28
Hauptverfasser:	Avrachenkov, Konstantin E., Kondratev, Aleksei Y., Mazalov, Vladimir V., Rubanov, Dmytro G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.12.2018 Springer Nature B.V Springer
Schlagworte:	Article Collection of the 6th International Conference on Complex Networks and Their Applications Communities Computer Science Data-driven Science Database Management Game theory Graph theory Industrial and Production Engineering Industrial Organization Machine Learning Mathematical Models of Cognitive Processes and Neural Networks Mathematics Mathematics and Statistics Media Sociology Modeling and Theory Building Modularity Social and Information Networks Statistics Network partitioning Community detection Gibbs sampling Hedonic game Myerson value Cooperative game
ISSN:	2197-4314, 2197-4314
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!