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The normalized Laplacian spectrum is a good indicator of connectivity for comparing graphs with different sizes (i.e., the number of nodes). This paper shows the performances of several random-walk sampling algorithms using the spectral indicator. Based on two types of complex network models with exponential and power-law degree distributions, we determine that the sampling algorithms do not perform...
Recent researches proposed that the weighted spectral distribution is a robust spectral metric independent of the network size (node number) and can be quickly calculated in large-scale networks using the graph structure of 4-cycles. In this paper, we design an algorithm for calculating the spectral metric within a more complex graph structure (i.e., 5-cycles) and two theorems are proposed to verify...
Evolving complex networks are abundant in the real world, i.e., Networks with different sizes (number of nodes) may originate from the same evolving system. In this paper, we use some typical evolving models of complex networks to evaluate the performances of graph spectra. The experimental results verify that the normalized Laplacian spectrum is a good indicator to distinguish between different evolving...
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