Node, Motif and Subgraph: Leveraging Network Functional Blocks Through Structural ConvolutionEI
Networks or graphs provide a natural and generic way for modeling rich structured data. Recent research on graph analysis has been focused on representation learning, of which the goal is to encode the network structures into distributed embedding vectors, so as to enable various downstream applications through off-the-shelf machine learning. However, existing methods mostly focus on node-level embedding, which is insufficient for subgraph analysis. Moreover, their leverage of network structures through path sampling or neighborhood p...更多
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ASONAM, pp. 47-52, 2018.