Abstract: One of the main issues in complex networks theory is to find
the “most important” nodes. To this aim, one can use matrix functions
applied to its adjacency matrix.
After an introduction on the use of Gauss-type quadrature rules, we will
discuss a new computational method to rank the nodes of both directed
and undirected (unweighted) networks according to the values of these
functions. The algorithm uses a low-rank approximation of the adjacency
matrix, then Gauss quadrature is used to refine the computation.
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