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Generating Realistic Labelled, Weighted Random Graphs
Generative algorithms for random graphs have yielded insights into the structure and evolution of real-world networks. Most networks exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Usually, random graph models consider only struc...
| Autores principales: | , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2015
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.3390/a8041143 http://cds.cern.ch/record/2118891 |