Table 1. Basic topological features of example networks.

Where, e is the efficiency of a network and defined as $e=\frac{2}{n(n-1)}{\displaystyle {\sum }_{i,j\in V,i\ne j}{l}_{ij}^{-1}}$ [51], c is clustering coefficient [4], r is assortative coefficient [33], h is degree heterogeneity and defined as $h=\frac{\langle k^2\rangle }{{\langle k\rangle }^2}$, where 〈k〉 is average degree of a network [16]. d is the diameter of a network. lcp is the correlation between LCP and CN indices presented in [3]. For more definitions and details of the mentioned topological measures, please reference to [51–53].

	n	m	e	c	r	h	d	lcp
USAir	332	2126	0.406	0.749	-0.208	3.46	6	0.9799
PB	1224	19090	0.397	0.361	-0.079	3.13	8	0.9286
INT	5022	6258	0.167	0.033	-0.138	5.05	15	0.8067
Neural	297	2148	0.308	0.2924	-0.1632	1.8008	5	0.9056
Word	112	425	0.442	0.1728	-0.1293	1.8149	5	0.8528
NS	1461	2742	0.016	0.878	0.462	1.85	17	0.9474
Grid	4941	6594	0.063	0.107	0.003	1.45	46	0.8456
FT	115	613	0.4504	0.4032	0.1624	1.01	4	0.8931
Email	1133	5451	0.2999	0.254	0.0782	1.94	8	0.8538
Jazz	198	2742	0.5132	0.633	0.0202	1.3951	6	0.9484