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Techniques

DeepWalk

May 2020
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DeepWalk is an algorithm that helps apply machine learning on graphs. When working on data sets that are represented as graphs, one of the key problems is to extract features from the graph. This is where DeepWalk can help. It uses SkipGram to construct node embeddings by viewing the graph as a language where each node is a unique word in the language and random walks of finite length on the graph constitutes a sentence. These embeddings can then be used by various ML models. DeepWalk is one of the techniques we're trialling on some of our projects where we've needed to apply machine learning on graphs.