DeepWalk: Online Learning of Social Representations

26 Mar 2014Bryan Perozzi • Rami Al-Rfou • Steven Skiena

We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs.

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Task Dataset Model Metric name Metric value Global rank Compare
Node Classification BlogCatalog DeepWalk Accuracy 22.50% # 3
Node Classification BlogCatalog DeepWalk Macro-F1 0.214 # 3
Node Classification Citeseer DeepWalk Accuracy 43.2% # 9
Node Classification Cora DeepWalk Accuracy 67.2% # 9
Node Classification NELL DeepWalk Accuracy 58.1% # 3
Node Classification Pubmed DeepWalk Accuracy 65.3% # 9
Node Classification Wikipedia DeepWalk Accuracy 19.40% # 3
Node Classification Wikipedia DeepWalk Macro-F1 0.183 # 3