A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions
Abstract Deep learning has seen significant growth recently and is now applied to a wide range of conventional use cases, including graphs. Graph data provides relational information between elements and is a standard data format for various machine learning and deep learning tasks. Models that can...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2024-01-01
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Series: | Journal of Big Data |
Subjects: | |
Online Access: | https://doi.org/10.1186/s40537-023-00876-4 |