Prediction of missing links and reconstruction of complex networks

Cheng-Jun Zhang and An Zeng ()
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Cheng-Jun Zhang: School of Computer & Software, Nanjing University of Information Science & Technology, No.219, Ningliu Road, Nanjing, Jiangsu 210044, P. R. China
An Zeng: School of Systems Science, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, Beijing, 100875, P. R. China

International Journal of Modern Physics C (IJMPC), 2016, vol. 27, issue 10, 1-12

Abstract: 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.

Keywords: Link prediction; complex networks; missing links; network properties (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1142/S0129183116501205

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