An intermediary probability model for link prediction

作者：Zhang, Xuejun; Pang, Wenbo; Xia, Yongxiang^*

来源：Physica A: Statistical Mechanics and Its Applications , 2018, 512: 902-912.

DOI：10.1016/j.physa.2018.08.068

• Complex networks
• Link prediction
• Intermediary probability model
• K-shell decomposition

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.

• 出版日期2018-12-15
• 单位北京航空航天大学; 浙江大学