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An intermediary probability model for link prediction

Xuejun Zhang, Wenbo Pang and Yongxiang Xia

Physica A: Statistical Mechanics and its Applications, 2018, vol. 512, issue C, 902-912

Abstract: Among the numerous link prediction algorithms in complex networks, similarity-based algorithms play an important role due to promising accuracy and low computational complexity. Apart from the classical CN-based indexes, several interdisciplinary methods provide new ideas to this problem and achieve improvements in some aspects. In this article, we propose a new model from the perspective of an intermediary process and introduce indexes under the framework, which show better performance for precision. Combined with k-shell decomposition, our deeper analysis gives a reasonable explanation and presents an insight on classical and proposed algorithms, which can further contribute to the understanding of link prediction problem.

Keywords: Complex networks; Link prediction; Intermediary probability model; K-shell decomposition (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:512:y:2018:i:c:p:902-912

DOI: 10.1016/j.physa.2018.08.068

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