metapath2vec: Scalable Representation Learning for Heterogeneous Networks

  title={metapath2vec: Scalable Representation Learning for Heterogeneous Networks},
  author={Yuxiao Dong and Nitesh V. Chawla and Ananthram Swami},
We study the problem of representation learning in heterogeneous networks. Its unique challenges come from the existence of multiple types of nodes and links, which limit the feasibility of the conventional network embedding techniques. We develop two scalable representation learning models, namely metapath2vec and metapath2vec++. The metapath2vec model formalizes meta-path-based random walks to construct the heterogeneous neighborhood of a node and then leverages a heterogeneous skip-gram… CONTINUE READING
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