Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5102873 | Physica A: Statistical Mechanics and its Applications | 2017 | 14 Pages |
Abstract
Predicting missing links is of both theoretical value and practical interest in network science. In this paper, we empirically investigate a new link prediction method base on similarity and compare nine well-known local similarity measures on nine real networks. Most of the previous studies focus on the accuracy, however, it is crucial to consider the link predictability as an initial property of networks itself. Hence, this paper has proposed a new link prediction approach called evidential measure (EM) based on Dempster-Shafer theory. Moreover, this paper proposed a new method to measure link predictability via local information and Shannon entropy.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Likang Yin, Haoyang Zheng, Tian Bian, Yong Deng,