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KBGAN: Adversarial Learning for Knowledge Graph Embeddings (N18-1)

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Challenge: Existing knowledge graph embedding techniques lack the capability to access similarities between entities and relations.
Approach: They propose an adversarial learning framework to improve knowledge graph embedding models . they use one knowledge graph embedded model as a negative sample generator .
Outcome: The proposed framework improves the performance of knowledge graph embedding models on a link prediction task.

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