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Revealing how network structure affects accuracy of link prediction

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Abstract

Link prediction plays an important role in network reconstruction and network evolution. The network structure affects the accuracy of link prediction, which is an interesting problem. In this paper we use common neighbors and the Gini coefficient to reveal the relation between them, which can provide a good reference for the choice of a suitable link prediction algorithm according to the network structure. Moreover, the statistical analysis reveals correlation between the common neighbors index, Gini coefficient index and other indices to describe the network structure, such as Laplacian eigenvalues, clustering coefficient, degree heterogeneity, and assortativity of network. Furthermore, a new method to predict missing links is proposed. The experimental results show that the proposed algorithm yields better prediction accuracy and robustness to the network structure than existing currently used methods for a variety of real-world networks.

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References

  1. R. Albert, A.L. Barabási, Rev. Mod. Phys. 74, (2002) 47

    Article  ADS  MathSciNet  Google Scholar 

  2. Q.M. Zhang, L. Lü, W.Q. Wang et al., PLoS ONE 8, e55437 (2013)

    Article  ADS  Google Scholar 

  3. W.Q. Wang, Q.M. Zhang, T. Zhou, EPL 98, 28004 (2012)

    Article  ADS  Google Scholar 

  4. Q.M. Zhang, X.K. Xu, Y.X. Zhu, T. Zhou, Sci. Rep. 5, 10350 (2015)

    Article  ADS  Google Scholar 

  5. Von C. Mering, R. Krause, B. Snel et al., Nature 417, 399 (2002)

    Article  ADS  Google Scholar 

  6. L.A.H. Amaral, Proc. Natl. Acad. Sci. USA 105, 6795 (2008)

    Article  ADS  Google Scholar 

  7. A.L. Barabási et al., Physica A 311, 590 (2002)

    Article  ADS  MathSciNet  Google Scholar 

  8. S.N. Dorogovtsev, J.F. Mendes, Adv. Phys. 51, 1079 (2002)

    Article  ADS  Google Scholar 

  9. B. Bringmann, M. Berlingerio, F. Bonchi, A. Gionis, IEEE Intell. Syst. 25, 26 (2010)

    Article  Google Scholar 

  10. H. Yu, P. Braun, M.A. Yildirim et al., Science 322, 104 (2008)

    Article  ADS  Google Scholar 

  11. M.P.H. Stumpf, T. Thorne et al., Proc. Natl. Acad. Sci. USA 105, 6959 (2008)

    Article  ADS  Google Scholar 

  12. L. Lü, M. Medo, C.H. Yeung et al., Phys. Rep. 519, 1 (2012)

    Article  ADS  Google Scholar 

  13. A. Fiasconaro, M. Tumminello, V. Nicosia et al., Phys. Rev. E 92, 012811 (2015)

    Article  ADS  Google Scholar 

  14. N. Rovira-Asenjo, T. Gumí, M. Sales-Pardo, R. Guimerà, Sci. Rep. 3, 1999 (2013)

    Article  ADS  Google Scholar 

  15. R. Guimerà, A. Llorente, E. Moro, M. Sales-Pardo, PLoS ONE 7, e44620 (2012)

    Article  ADS  Google Scholar 

  16. L. Lü, T. Zhou, Physica A 390, 1150 (2011)

    Article  ADS  Google Scholar 

  17. T. Zhou, L. Lü, Y.C. Zhang, Eur. Phys. J. B 71, 623 (2009)

    Article  ADS  Google Scholar 

  18. L. Lü, C.H. Jin, T. Zhou, Phys. Rev. E 80, 046122 (2009)

    Article  ADS  Google Scholar 

  19. R. Merris, Linear Algebra Appl. 197, 143 (1994)

    Article  MathSciNet  Google Scholar 

  20. M.E.J. Newman, Phys. Rev. E 67, 026126 (2003)

    Article  ADS  MathSciNet  Google Scholar 

  21. V. Sood, S. Redner, Phys. Rev. Lett. 94, 178701 (2005)

    Article  ADS  Google Scholar 

  22. D.J. Watts, S.H. Strogatz, Nature 393, 440 (1998)

    Article  ADS  Google Scholar 

  23. A.L. Barabási, R. Albert, Science 286, 509 (1999)

    Article  ADS  MathSciNet  Google Scholar 

  24. W.W. Zachary, J. Anthropol. Res. 33, 452 (1977)

    Article  Google Scholar 

  25. R. Milo, S. Itzkovitz, N. Kashtan et al., Science 303, 1538 (2004)

    Article  ADS  Google Scholar 

  26. D. Lusseau et al., Behav. Ecol. Sociobiol. 54, 396 (2003)

    Article  Google Scholar 

  27. D.E. Knuth, The Stanford GraphBase: A Platform for Combinatorial Computing (Addison-Wesley, Reading, MA, 1993)

  28. M.E.J. Newman, Phys. Rev. E 74, 036104 (2006)

    Article  ADS  MathSciNet  Google Scholar 

  29. M. Girvan, M.E.J. Newman, Proc. Natl. Acad. Sci. USA 99, 7821 (2002)

    Article  ADS  MathSciNet  Google Scholar 

  30. P. Gleiser, L. Danon, Adv. Complex Syst. 6, 565 (2003)

    Article  Google Scholar 

  31. J. Duch, A. Arenas, Phys. Rev. E 72, 027104 (2005)

    Article  ADS  Google Scholar 

  32. R. Milo, S. Shen-Orr, S. Itzkovitz et al., Science 298, 824 (2002)

    Article  ADS  Google Scholar 

  33. R. Guimera, L. Danon, A. Diaz-Guilera et al., Phys. Rev. E 68, 065103 (2003)

    Article  ADS  Google Scholar 

  34. L.A. Adamic, N. Glance, in 3rd Int. Workshop on Link Discov., ACM, 2005, pp. 36–43

  35. T. Ogwang, Oxford Bull. Econ. Stat. 62, 123 (2000)

    Article  Google Scholar 

  36. A.E. Brouwer, W.H. Haemers, Spectra of Graphs (New York, Springer, 2011)

  37. A.L. Barabási, R. Albert, Science 286, 509 (1999)

    Article  ADS  MathSciNet  Google Scholar 

  38. S. Zhou, R.J. Mondragón, IEEE Commun. Lett. 8, 180 (2004)

    Article  Google Scholar 

  39. V. Colizza, A. Flammini, M.A. Serrano, A. Vespignani, Nat. Phys. 2, 110 (2006)

    Article  Google Scholar 

  40. M. Boguná, R. Pastor-Satorras, Phys. Rev. E 64, 047104 (2002)

    Article  ADS  Google Scholar 

  41. J.A. Hanley, B.J. McNeil, Radiology 143, 29 (1982)

    Article  Google Scholar 

  42. E.A. Leicht, P. Holme, M.E.J. Newman, Phys. Rev. E 73, 026120 (2006)

    Article  ADS  Google Scholar 

  43. B. He, L. Gu, X.D. Zhang, J. Stat. Mech. 2012, P02012 (2012)

    Google Scholar 

Download references

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Authors and Affiliations

  1. School of Mathematical Sciences, MOE-LSC and SHL-MAC, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, P.R. China

    Jin-Xuan Yang & Xiao-Dong Zhang

Authors
  1. Jin-Xuan Yang
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  2. Xiao-Dong Zhang
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Correspondence to Xiao-Dong Zhang.

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Yang, JX., Zhang, XD. Revealing how network structure affects accuracy of link prediction. Eur. Phys. J. B 90, 157 (2017). https://doi.org/10.1140/epjb/e2017-70599-4

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  • DOI: https://doi.org/10.1140/epjb/e2017-70599-4

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