A Graph Representation Learning Framework Predicting Potential Multivariate Interactions

A Graph Representation Learning Framework Predicting Potential Multivariate Interactions

Abstract Link prediction is a widely adopted method for extracting valuable data insights from graphs, primarily aimed at predicting interactions between two nodes. However, there are not only pairwise interactions but also multivariate interactions in real life. For example, reactions between multi...

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Bibliographic Details
Main Authors: Yanlin Yang, Zhonglin Ye, Haixing Zhao, Lei Meng
Format: Article
Language:English
Published: Springer 2023-09-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Hypergraph
Hyperlink prediction
Multivariate interactions
Graph representation learning
Biological metabolic reaction network
Organic chemical reaction network
Online Access:https://doi.org/10.1007/s44196-023-00329-z

Internet

https://doi.org/10.1007/s44196-023-00329-z

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