Revealing how network structure affects accuracy of link prediction
Jin-Xuan Yang and
Xiao-Dong Zhang ()
Additional contact information
Jin-Xuan Yang: School of Mathematical Sciences, MOE-LSC and SHL-MAC, Shanghai Jiao Tong University
Xiao-Dong Zhang: School of Mathematical Sciences, MOE-LSC and SHL-MAC, Shanghai Jiao Tong University
The European Physical Journal B: Condensed Matter and Complex Systems, 2017, vol. 90, issue 8, 1-8
Abstract:
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.
Keywords: Statistical; and; Nonlinear; Physics (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1140/epjb/e2017-70599-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:eurphb:v:90:y:2017:i:8:d:10.1140_epjb_e2017-70599-4
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/10051
DOI: 10.1140/epjb/e2017-70599-4
Access Statistics for this article
The European Physical Journal B: Condensed Matter and Complex Systems is currently edited by P. Hänggi and Angel Rubio
More articles in The European Physical Journal B: Condensed Matter and Complex Systems from Springer, EDP Sciences
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().