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Group Representation Theory for Knowledge Graph Embedding

2019-09-11 · Chen Cai

Knowledge graph embedding has recently become a popular way to model relations and infer missing links. In this paper, we present a group theoretical perspective of knowledge graph embedding, connecting previous methods with different group actions. Furthermore, by utilizing Schur's lemma from group representation theory, we show that the state of the art embedding method RotatE can model relations from any finite Abelian group.

📄 PDF Abstract BibTeX arXiv:1909.05100

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Graph EmbeddingKnowledge Graph EmbeddingLEMMA

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Self-Adversarial Negative Sampling 설명 없음
RotatE RotatE is a method for generating graph embeddings which is able to model and infer various relation patterns including: symmetry/antisymmetry, inversion, and composition.…

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