Method for quickly inferring the mechanisms of large-scale complex networks based on the census of subgraph concentrations

被引:1
|
作者
Yang, Bo [1 ]
Chen, Xiaorong [2 ]
机构
[1] Hangzhou Dianzi Univ, Sch Management, Hangzhou 310018, Peoples R China
[2] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200030, Peoples R China
基金
中国国家自然科学基金;
关键词
Large-scale complex networks; mechanism-inferring; model evaluation; subgraph census; ALGORITHM;
D O I
10.1007/s11424-009-9161-y
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
A Mechanism-Inferring method of networks exploited from machine learning theory can effectively evaluate the predicting performance of a network model. The existing method for inferring network mechanisms based on a census of subgraph numbers has some drawbacks, especially the need for a runtime increasing strongly with network size and network density. In this paper, an improved method has been proposed by introducing a census algorithm of subgraph concentrations. Network mechanism can be quickly inferred by the new method even though the network has large scale and high density. Therefore, the application perspective of mechanism-inferring method has been extended into the wider fields of large-scale complex networks. By applying the new method to a case of protein interaction network, the authors obtain the same inferring result as the existing method, which approves the effectiveness of the method.
引用
收藏
页码:252 / 259
页数:8
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