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Deep Link-Prediction Based on the Local Structure of Bipartite Networks

1
School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
2
School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai 201209, China
*
Author to whom correspondence should be addressed.
Academic Editor: Donald J. Jacobs
Entropy 2022, 24(5), 610; https://doi.org/10.3390/e24050610
Received: 29 March 2022 / Revised: 21 April 2022 / Accepted: 26 April 2022 / Published: 27 April 2022
(This article belongs to the Topic Complex Systems and Artificial Intelligence)
Link prediction based on bipartite networks can not only mine hidden relationships between different types of nodes, but also reveal the inherent law of network evolution. Existing bipartite network link prediction is mainly based on the global structure that cannot analyze the role of the local structure in link prediction. To tackle this problem, this paper proposes a deep link-prediction (DLP) method by leveraging the local structure of bipartite networks. The method first extracts the local structure between target nodes and observes structural information between nodes from a local perspective. Then, representation learning of the local structure is performed on the basis of the graph neural network to extract latent features between target nodes. Lastly, a deep-link prediction model is trained on the basis of latent features between target nodes to achieve link prediction. Experimental results on five datasets showed that DLP achieved significant improvement over existing state-of-the-art link prediction methods. In addition, this paper analyzes the relationship between local structure and link prediction, confirming the effectiveness of a local structure in link prediction. View Full-Text
Keywords: link prediction; bipartite network; local structure; representation learning link prediction; bipartite network; local structure; representation learning
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MDPI and ACS Style

Lv, H.; Zhang, B.; Hu, S.; Xu, Z. Deep Link-Prediction Based on the Local Structure of Bipartite Networks. Entropy 2022, 24, 610. https://doi.org/10.3390/e24050610

AMA Style

Lv H, Zhang B, Hu S, Xu Z. Deep Link-Prediction Based on the Local Structure of Bipartite Networks. Entropy. 2022; 24(5):610. https://doi.org/10.3390/e24050610

Chicago/Turabian Style

Lv, Hehe, Bofeng Zhang, Shengxiang Hu, and Zhikang Xu. 2022. "Deep Link-Prediction Based on the Local Structure of Bipartite Networks" Entropy 24, no. 5: 610. https://doi.org/10.3390/e24050610

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