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Deep Feature Learning of Multi-Network Topology for Node Classification
[article]
2018
arXiv
pre-print
Networks are ubiquitous structure that describes complex relationships between different entities in the real world. As a critical component of prediction task over nodes in networks, learning the feature representation of nodes has become one of the most active areas recently. Network Embedding, aiming to learn non-linear and low-dimensional feature representation based on network topology, has been proved to be helpful on tasks of network analysis, especially node classification. For many
arXiv:1809.02394v1
fatcat:2egjudinvncfdgfz5su7rjxmza