Papers with knowledge graph embedding model
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. |
Differentiating Concepts and Instances for Knowledge Graph Embedding (D18-1)
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| Challenge: | Existing knowledge graph embedding methods encode concepts and instances as vectors in a low-dimensional space, ignoring the difference between concepts and instance. |
| Approach: | They propose a knowledge graph embedding model that separates concepts from instances by differentiating concepts and instances. |
| Outcome: | The proposed model outperforms state-of-the-art methods on link prediction and triple classification tasks on YAGO dataset. |