node2vec: Scalable Feature Learning for Networks

@article{Grover2016node2vecSF,
  title={node2vec: Scalable Feature Learning for Networks},
  author={Aditya Grover and Jure Leskovec},
  journal={KDD : proceedings. International Conference on Knowledge Discovery & Data Mining},
  year={2016},
  volume={2016},
  pages={
          855-864
        }
}
Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning… CONTINUE READING

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