SFGCN: Synergetic fusion-based graph convolutional networks approach for link prediction in social networks-Reference-Cited by-同舟云学术

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SFGCN: Synergetic fusion-based graph convolutional networks approach for link prediction in social networks

Published:2025-02 Issue: Volume:114 Page:102684
ISSN:1566-2535
Container-title:Information Fusion
language:en
Short-container-title:Information Fusion

Author:

Lee Sang-Woong,Tanveer Jawad,Rahmani Amir Masoud,Alinejad-Rokny Hamid,Khoshvaght Parisa,Zare Gholamreza,Malekpour Alamdari Pegah,Hosseinzadeh Mehdi

Publisher

Elsevier BV

Reference68 articles.

1. Recommendation of users in social networks: a semantic and social based classification approach;Berkani;Expert Syst.,2021

2. Social network analysis: a survey on process, tools, and application;Singh;ACM Comput. Surveys,2024

3. Graph regularized autoencoding-inspired non-negative matrix factorization for link prediction in complex networks using clustering information and biased random walk;Li;J. Supercomput.,2024

4. A hybrid clustering approach for link prediction in heterogeneous information networks;Sajjadi;Knowledge and Inf. Syst.,2023

5. Link prediction based on the mutual information with high-order clustering structure of nodes in complex networks;Yao;Physica A,2023

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