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DeepWalk-Turning Graphs Into Features via Network Embeddings

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3 June 2019


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DeepWalk: Turning Graphs Into Features via Network Embeddings

Abstract

  • Dr. Steven Skiena, Stony Brook University
  • Michael Hunger, Neo4j

Random walk algorithms help better model real-world scenarios, and when applied to graphs, can significantly improve machine learning. Learn how the Deepwalk supervised learning algorithm transfers deep learning techniques from natural language processing to network analysis, and explore the motivations behind graph-enhanced machine learning.


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