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| Link Predictability in Complex Networks |
| XU Xiao-ke1, XU Shuang1, ZHU Yu-xiao2, ZHANG Qian-ming2
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1. College of Information and Communication Engineering, Dalian Nationalities University, Dalian 116600, China;
2. Web Science Center, University of Electronic Science and Technology of China, Chengdu 610054, China |
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Abstract Link predictability in complex networks refers to the upper limit for link prediction accuracy by using prediction algorithm, and the analysis of link predictability is conductive to compare the pros and cons for various prediction methods in theory. In this paper, we analyzed the topological distance distribution between two nodes forming a link during the process of multiple networks evolution, and then illustrated the mechanism for making effective link prediction based on common neighbor similarity index. At last, we analyzed the prediction upper limit （predictability) for nine algorithms based on common neighbor similarity in theory. By analyzing the limitation of first order neighbor prediction algorithm and the factor affecting link predictability, we proposed two types of link prediction algorithms based on high order path information and calculated their predictability index. This study proposed the link predictability index in theory, and proved the validity of the proposed link prediction algorithm by predicting real networks.
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Received: 30 June 2013
Published: 22 June 2026
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