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This short talk given in Stockholm, Sweden, explains how algorithmic complexity measures, notably Kolmogorov complexity approximated both by lossless compression algorithms and the Block Decomposition Method (BDM) are capable of characterizing graphs and networks by some of their grouptheoretic and topological properties, notably graph automorphism group size and clustering coefficients of complex networks. The method distinguished between models of networks such as regular, random, smallworld and scalefree.
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