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Semi-Supervised Learning on Graphs Based on Local Label Distributions
Precisely, we propose a new node embedding which is based on the class labels in the local neighborhood of a node.
LASAGNE: Locality And Structure Aware Graph Node Embedding
For larger graphs with flat NCPs that are strongly expander-like, existing methods lead to random walks that expand rapidly, touching many dissimilar nodes, thereby leading to lower-quality vector representations that are less useful for downstream tasks.
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