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Metric Distribution to Vector: Constructing Data Representation via Broad-Scale Discrepancies
Graph embedding provides a feasible methodology to conduct pattern classification for graph-structured data by mapping each data into the vectorial space.
Graph Classification Based on Skeleton and Component Features
Most existing popular methods for learning graph embedding only consider fixed-order global structural features and lack structures hierarchical representation.
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