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Predicting missing links via effective paths

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  • Zhu, Xuzhen
  • Tian, Hui
  • Cai, Shimin

Abstract

Recently, in complex network, link prediction has brought a surge of researches, among which similarity based link prediction outstandingly gains considerable success, especially similarity in terms of paths. In investigation of paths based similarity, we find that the effective influence of endpoints and strong connectivity make paths contribute more similarity between two unconnected endpoints, leading to a more accurate link prediction. Accordingly, we propose a so-called effective path index (EP) in this paper to leverage effective influence of endpoints and strong connectivity in similarity calculation. For demonstrating excellence of our index, the comparisons with six mainstream indices are performed on experiments in 15 real datasets and results show a great improvement of performance via our index.

Suggested Citation

  • Zhu, Xuzhen & Tian, Hui & Cai, Shimin, 2014. "Predicting missing links via effective paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 515-522.
    • Handle: RePEc:eee:phsmap:v:413:y:2014:i:c:p:515-522
    DOI: 10.1016/j.physa.2014.07.029
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    Citations

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    Cited by:

    1. Lawford, Steve & Mehmeti, Yll, 2020. "Cliques and a new measure of clustering: With application to U.S. domestic airlines," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    2. Wu, Tao & Chen, Leiting & Zhong, Linfeng & Xian, Xingping, 2017. "Enhanced collective influence: A paradigm to optimize network disruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 43-52.
    3. Kumar, Ajay & Mishra, Shivansh & Singh, Shashank Sheshar & Singh, Kuldeep & Biswas, Bhaskar, 2020. "Link prediction in complex networks based on Significance of Higher-Order Path Index (SHOPI)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    4. Yao, Yabing & Zhang, Ruisheng & Yang, Fan & Tang, Jianxin & Yuan, Yongna & Hu, Rongjing, 2018. "Link prediction in complex networks based on the interactions among paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 52-67.
    5. Liu, Shuxin & Ji, Xinsheng & Liu, Caixia & Bai, Yi, 2017. "Extended resource allocation index for link prediction of complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 174-183.
    6. Wu, Tao & Chen, Leiting & Zhong, Linfeng & Xian, Xingping, 2017. "Predicting the evolution of complex networks via similarity dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 662-672.

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