Semantically Smooth Knowledge Graph Embedding

  title={Semantically Smooth Knowledge Graph Embedding},
  author={Shu Guo and Quan Wang and Bin Wang and Lihong Wang and Li Guo},
This paper considers the problem of embedding Knowledge Graphs (KGs) consisting of entities and relations into lowdimensional vector spaces. Most of the existing methods perform this task based solely on observed facts. The only requirement is that the learned embeddings should be compatible within each individual fact. In this paper, aiming at further discovering the intrinsic geometric structure of the embedding space, we propose Semantically Smooth Embedding (SSE). The key idea of SSE is to… CONTINUE READING
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