Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.
PLoS One. 2013;8(2):e55437. doi: 10.1371/journal.pone.0055437. Epub 2013 Feb 11.
Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation.
揭示网络形成的因素是数据挖掘和网络分析的长期挑战。特别是，有向网络的微观组织原则比无向网络的组织原则理解得更少。本文提出了一个名为势能理论的假设，该假设假设每条有向链路对应于一个单位势能的减少，并且具有所有节点可定义势能值的子图是首选的。将势能理论与聚类和同质性机制相结合，可以推断出由 4 个节点和 4 条有向链路组成的双扇出结构是有向网络中最受欢迎的局部结构。我们的假设在来自不同领域的 15 个有向网络上进行的广泛实验中得到了强烈的支持，双扇出预测器在链接预测框架内的最准确和最稳健的性能表明了这一点。总之，我们的主要贡献有两个方面：（i）我们提出了一个新的有向网络局部组织机制；（ii）我们设计了相应的链接预测算法，该算法不仅可以验证我们的假设，而且还可以在缺失链接预测和友谊推荐中找到直接应用。
