Effect of weak ties on degree and H-index in link prediction of complex network

Author:

Jia Jianlin1ORCID,Chen Yanyan1,Li Yongxing2,Li Tongfei1,Chen Ning1,Zhu Xuzhen3

Affiliation:

1. Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China

2. School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore

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

Abstract

Link prediction of complex network intends to estimate the probability of existence of links between two nodes. In order to improve link prediction accuracy and fully exploit the potentialities of nodes, many studies focus more on the influence of degree on nodes but less on the hybrid influence of degree and H-index. The nodes with a larger degree have more neighbors, and the nodes with larger H-index have more neighbors of neighbors. Meanwhile, weak ties consisting of neighbors with a small degree have powerful strength of intermediary ability and a high probability of passing similarity. A novel link prediction model is proposed considering the hybrid influence of degree and H-index and weak ties, which is called Hybrid Weak Influence, marked as HWI. After experimenting with nine real datasets, the results show that this method can significantly improve the link prediction accuracy, compared with the empirical methods: Common Neighbors (CN), Resource-Allocation (RA) and Adamic/Adar (AA). Meanwhile, the computation complexity is less than the long path algorithm of LP, SRW, PCEN.

Funder

Key Technology Research and Development Program of Shandong

Research Institute of Highway Ministry of Transport Open Project Funding

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

Cited by 3 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. Evaluation of information diffusion path based on a multi-topic relationship strength network;Knowledge and Information Systems;2022-12-17

2. Link Prediction Model for Weighted Networks Based on Evidence Theory and the Influence of Common Neighbours;Complexity;2022-03-01

3. A complex network modeling for job-shop manufacturing system;2022 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS);2022-03

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