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Prediction of missing links and reconstruction of complex networks

Author

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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)

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.

Suggested Citation

  • Cheng-Jun Zhang & An Zeng, 2016. "Prediction of missing links and reconstruction of complex networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(10), pages 1-12, October.
    • Handle: RePEc:wsi:ijmpcx:v:27:y:2016:i:10:n:s0129183116501205
    DOI: 10.1142/S0129183116501205
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    Citations

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    Cited by:

    1. Mingshuo Nie & Dongming Chen & Dongqi Wang, 2022. "Graph Embedding Method Based on Biased Walking for Link Prediction," Mathematics, MDPI, vol. 10(20), pages 1-13, October.
    2. Yin, Likang & Deng, Yong, 2018. "Toward uncertainty of weighted networks: An entropy-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 176-186.
    3. Yin, Likang & Zheng, Haoyang & Bian, Tian & Deng, Yong, 2017. "An evidential link prediction method and link predictability based on Shannon entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 699-712.
    4. Chengjun Zhang & Jin Liu & Yanzhen Qu & Tianqi Han & Xujun Ge & An Zeng, 2018. "Enhancing the robustness of recommender systems against spammers," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-14, November.

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