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Ensemble method: Community detection based on game theory.
- Source :
- International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics; 12/10/2014, Vol. 28 Issue 30, p1-18, 18p, 22 Diagrams, 2 Charts
- Publication Year :
- 2014
-
Abstract
- Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better. [ABSTRACT FROM AUTHOR]
- Subjects :
- GAME theory
COST effectiveness
SOCIAL networks
ALGORITHMS
GOVERNMENT policy
Subjects
Details
- Language :
- English
- ISSN :
- 02179792
- Volume :
- 28
- Issue :
- 30
- Database :
- Complementary Index
- Journal :
- International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics
- Publication Type :
- Academic Journal
- Accession number :
- 99859570
- Full Text :
- https://doi.org/10.1142/S0217979214502117