Shypd.aiThe largest open index of AI toolsDeepWalk is an open-source graph embedding technique that learns latent representations of nodes in graphs. It uses random walks to generate node sequences, which are then used to train a Skip-Gram model for various downstream tasks.
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DeepWalk is an open-source tool designed for learning latent representations of vertices within graphs. It achieves this by employing short random walks to generate sequences of nodes, which are subsequently used to train a Skip-Gram model. The resulting embeddings can be utilized for a variety of downstream tasks, such as multi-label node classification. The tool provides clear usage examples, including how to process different input formats like adjacency lists, edge lists, and Matlab .mat files. DeepWalk also offers evaluation guidelines, demonstrating how to reproduce results from its associated research paper, including performance metrics like Micro-F1 and Macro-F1 scores. It is based on gensim and requires numpy and scipy, with installation instructions provided for easy setup.
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