Reducing redundant information to find simplifying patterns in data sets and complex networks is a scientific challenge in many knowledge fields. Moreover, detecting the dimensionality of the data is still a hard-to-solve problem. An article published in the journal Nature Communications presents a method to infer the dimensionality of complex networks through the application of hyperbolic geometrics, which capture the complexity of relational structures of the real world in many diverse domains.
Among the authors of the study are the researchers M. Ángeles Serrano and Marián Boguñá,…
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