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Multimodal Deep Network Embedding with Integrated Structure and Attribute Information
[article]
2019
arXiv
pre-print
Network embedding is the process of learning low-dimensional representations for nodes in a network, while preserving node features. Existing studies only leverage network structure information and focus on preserving structural features. However, nodes in real-world networks often have a rich set of attributes providing extra semantic information. It has been demonstrated that both structural and attribute features are important for network analysis tasks. To preserve both features, we
arXiv:1903.12019v1
fatcat:p5h3ubyzvjf6lg35rj2ca22bei