In this paper, we relatively extend the definition of the global clustering coefficient to another clustering, which we call it \emph{relative clustering coefficient}. The idea of this definition is to ignore the edges in the network that the probability of having an edge is $0$. Here, we also consider a model as an example that using the relative clustering coefficient is better than the global clustering coefficient for comparing networks and also checking the properties of the networks.
Touli, E., & Lindberg, O. (2022). Relative Clustering Coefficient. Journal of Algorithms and Computation, 54(1), 99-108. https://doi.org/10.22059/jac.2022.88373
MLA
Touli, E., & Lindberg, O. "Relative Clustering Coefficient", Journal of Algorithms and Computation, 54, 1, 2022, 99-108. doi: 10.22059/jac.2022.88373
HARVARD
Touli E., Lindberg O. (2022). 'Relative Clustering Coefficient', Journal of Algorithms and Computation, 54(1), pp. 99-108. doi: 10.22059/jac.2022.88373
CHICAGO
E. Touli & O. Lindberg, "Relative Clustering Coefficient," Journal of Algorithms and Computation, 54 1 (2022): 99-108, doi: 10.22059/jac.2022.88373
VANCOUVER
Touli E., Lindberg O. Relative Clustering Coefficient. J. Algo. Comp. 2022;54(1):99-108. doi: 10.22059/jac.2022.88373
