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Random Walk in Node Embeddings (DeepWalk, node2vec, LINE, and GraphSAGE)
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Random Walk in Node Embeddings (DeepWalk, node2vec, LINE, and GraphSAGE)

Last Updated on July 20, 2023 by Editorial Team

Author(s): Edward Ma

Originally published on Towards AI.

Graph Embeddings

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Photo by Steven Wei on Unsplash

Instead of using traditional machine learning classification tasks, we can consider using graph neural network (GNN) to perform node classification problems. By providing an explicit link of nodes, this classification problem is no longer classified as an independent problem but leveraging graph structures such as the degree of nodes. The usefulness of graph properties assumes that individual nodes are correlated with other similar nodes.

Typically example is a social media network. Imagine how Facebook connects you and somebody else based on what post you like, where you check-in etc. A graph is capable to represent… Read the full blog for free on Medium.

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