Heterogeneous Information Network Embedding for Meta Path based Proximity

A network embedding is a representation of a large graph in a low-dimensional space, where vertices are modeled as vectors. The objective of a good embedding is to preserve the proximity between vertices in the original graph. This way, typical search and mining methods can be applied in the embedded space with the help of off-the-shelf multidimensional indexing approaches. Existing network embedding techniques focus on homogeneous networks, where all vertices are considered to belong to a single class.

• Publication year

  2017

• Venue

  arXiv.org

• Publication date

  2017-01-19

• Fields of study

  Computer Science

• Identifiers
  arXiv 1701.05291
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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