Table 2.

Comparison of the execution time of some real networks.

Type	Name	N	L	n pd	t new (sec)	t old (sec)	Speedup
Biological	E. Coli 30	423	578	0.730	0.001	0.016	16.0
	TRN-Yeast-131	4441	12873	0.999	0.015	0.062	4.1
	TRN-Yeast-232	688	1079	0.920	0.001	0.015	15.0
	Human PPI33	6339	34814	0.585	0.032	1.295	40.5
Trust	Slashdot090234	82168	948464	0.912	0.421	1568.3	3725.2
	Slashdot081134	77360	905468	0.910	0.234	1388.9	5935.5
	WikiVote35	7115	103689	0.666	0.047	2.044	43.5
	SciMet36	3084	10416	0.661	0.015	0.187	12.5
	Kohonen37	4470	12731	0.669	0.016	0.172	10.8
Internet	p2p-138	10876	39994	0.911	0.062	2.746	44.3
	p2p-238	8846	31839	0.926	0.046	1.732	37.6
	p2p-338	8717	31525	0.933	0.031	1.700	54.8
Product co-purchasing	Amazon030239	262111	1234877	0.177	1.685	14119.4	8379.5
	Amazon031239	400727	3200440	0.127	9.344	36696	3927.2
	Amazon050539	410236	3356824	0.915	7.519	45453	6045.2
	Amazon060139	403394	3387388	0.053	2.886	49293	17080.1
Social network	Twitter40	81306	1768149	0.800	2.230	2532.5	1135.6
	Higgs_Twitter41	456626	14855842	0.297	12.589	66445.2	5278.0
	UClonline42	1899	20296	0.819	0.016	0.296	18.5
	Facebook_34840	572	6384	0.612	0.001	0.062	62.0

For each network, we show its type, name, number of nodes (N) and edges (L), density of all possible input nodes n _pd, the execution time of our method t _new, the execution time of previous algorithm²² t _old, and the speedup ratio.