Link prediction based on hybrid influence of neighbors

Author:

Gao Tianrun1ORCID,Zhu Xuzhen2

Affiliation:

1. College of Engineering, Northeastern University, Boston, MA 02115, USA

2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, P. R. China

Abstract

In previous link prediction researches, most scholars evaluate the influence of endpoints by the degree or H-index of endpoints, resulting in limited prediction accuracy. Through abundant investigations, we can evaluate the influence of endpoints accurately by the hybrid influence of neighbor nodes. Meanwhile, we calculate the hybrid influence of neighbors (HIN) by the average values of degree and H-index. In the paper, we conceive a HIN model. Large-scale experiments on 12 real datasets indicate that the conceived methods can significantly enhance the accuracy of link prediction.

Funder

National Natural Science Foundation of China

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Asymmetric influence-based superposed random walk link prediction algorithm in complex networks;International Journal of Modern Physics C;2024-05-18

2. Nearest neighbor walk network embedding for link prediction in complex networks;Physica A: Statistical Mechanics and its Applications;2023-06

3. Detecting Communities in Complex Networks Using an Adaptive Genetic Algorithm and Node Similarity-Based Encoding;Complexity;2023-02-28

4. Hybrid influence based on diversity of degree and H-index of neighbors;Third International Conference on Computer Science and Communication Technology (ICCSCT 2022);2022-12-29

5. Hierarchy-entropy based method for command and control networks reconfiguration;The Journal of Supercomputing;2022-04-15

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