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Predicting link directions using local directed path

Author

Listed:
  • Wang, Xiaojie
  • Zhang, Xue
  • Zhao, Chengli
  • Xie, Zheng
  • Zhang, Shengjun
  • Yi, Dongyun

Abstract

Link prediction in directed network is attracting growing interest among many network scientists. Compared with predicting the existence of a link, determining its direction is more complicated. In this paper, we propose an efficient solution named Local Directed Path to predict link direction. By adding an extra ground node to the network, we solve the information loss problem in sparse network, which makes our method effective and robust. As a quasi-local method, our method can deal with large-scale networks in a reasonable time. Empirical analysis on real networks shows that our method can correctly predict link directions, which outperforms some local and global methods.

Suggested Citation

  • Wang, Xiaojie & Zhang, Xue & Zhao, Chengli & Xie, Zheng & Zhang, Shengjun & Yi, Dongyun, 2015. "Predicting link directions using local directed path," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 260-267.
    • Handle: RePEc:eee:phsmap:v:419:y:2015:i:c:p:260-267
    DOI: 10.1016/j.physa.2014.10.007
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    References listed on IDEAS

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    1. Qian-Ming Zhang & Linyuan Lü & Wen-Qiang Wang & Yu-Xiao & Tao Zhou, 2013. "Potential Theory for Directed Networks," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-8, February.
    2. Xie, Zheng & Dong, Enming & Li, Jianping & Kong, Dexing & Wu, Ning, 2014. "Potential links by neighbor communities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 244-252.
    3. Zhang, Xue & Wang, Xiaojie & Zhao, Chengli & Yi, Dongyun & Xie, Zheng, 2014. "Degree-corrected stochastic block models and reliability in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 553-559.
    4. Armstrong, Mark, 1998. "Network Interconnection in Telecommunications," Economic Journal, Royal Economic Society, vol. 108(448), pages 545-564, May.
    5. Guo, Fangjian & Yang, Zimo & Zhou, Tao, 2013. "Predicting link directions via a recursive subgraph-based ranking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3402-3408.
    6. Aaron Clauset & Cristopher Moore & M. E. J. Newman, 2008. "Hierarchical structure and the prediction of missing links in networks," Nature, Nature, vol. 453(7191), pages 98-101, May.
    7. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    8. Tao Zhou & Linyuan Lü & Yi-Cheng Zhang, 2009. "Predicting missing links via local information," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 623-630, October.
    9. Yanbo Zhou & Linyuan Lü & Weiping Liu & Jianlin Zhang, 2013. "The Power of Ground User in Recommender Systems," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-11, August.
    10. Li, Qian & Zhou, Tao & Lü, Linyuan & Chen, Duanbing, 2014. "Identifying influential spreaders by weighted LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 47-55.
    11. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    12. Lämmer, Stefan & Gehlsen, Björn & Helbing, Dirk, 2006. "Scaling laws in the spatial structure of urban road networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 89-95.
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    Cited by:

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