Multilayer network simplification: approaches, models and methods

@article{Interdonato2020MultilayerNS,
  title={Multilayer network simplification: approaches, models and methods},
  author={Roberto Interdonato and Matteo Magnani and D. Perna and A. Tagarelli and Davide Vega},
  journal={Comput. Sci. Rev.},
  year={2020},
  volume={36},
  pages={100246}
}
Abstract Multilayer networks have been widely used to represent and analyze systems of interconnected entities where both the entities and their connections can be of different types. However, real multilayer networks can be difficult to analyze because of irrelevant information, such as layers not related to the objective of the analysis, because of their size, or because traditional methods defined to analyze simple networks do not have a straightforward extension able to handle multiple… Expand
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References

SHOWING 1-10 OF 152 REFERENCES
Structural reducibility of multilayer networks.
Core Decomposition and Densest Subgraph in Multilayer Networks
Multilayer networks
Principled Multilayer Network Embedding
Multilayer Social Networks
Relating modularity maximization and stochastic block models in multilayer networks
Multilayer Analysis and Visualization of Networks
Random walk centrality in interconnected multilayer networks
Community Structure in Time-Dependent, Multiscale, and Multiplex Networks
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