摘要
Predicting missing links in complex networks is of great significance from both theoretical and practical point of view, which not only helps us understand the evolution of real systems but also relates to many applications in social, biological and online systems. In this paper, we study the features of different simple link prediction methods, revealing that they may lead to the distortion of networks’ structural and dynamical properties. Moreover, we find that high prediction accuracy is not definitely corresponding to a high performance in preserving the network properties when using link prediction methods to reconstruct networks. Our work highlights the importance of considering the feedback effect of the link prediction methods on network properties when designing the algorithms.
摘要译文
在复杂的网络预测缺少的环节是从理论和实践两个角度来看，这不仅有助于我们了解真正的系统的发展具有重大意义，但也涉及到许多应用程序在社会，生物和在线systemsIn本文中，我们研究不同的简单的链接预测方法的特点，揭示了它们可能会导致网络鈥结构和动力学propertiesMoreover的失真，我们发现，较高的预测精度也不是明确对应于高性能使用链接时保持网络属性预测方法，以重建networksOur工作突出了设计算法时考虑对网络性能的链接预测方法的反馈效应的重要性
Cheng-Jun Zhang[1] An Zeng[2]. Prediction of missing links and reconstruction of complex networks[J]. International Journal of Modern Physics C: Computational Physics and Physical Computation, 2016,27(10): 12