Papers with KG embedding model
MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering (2022.acl-srw)
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| Challenge: | Existing methods to embed learning use a standard Neural Networks (NN) backward mechanism, duplicating its memory consumption. |
| Approach: | They propose a memory-efficient KG embedding model that embeds knowledge graphs as 3rd-order binary tensors. |
| Outcome: | The proposed model yields comparable performance on link prediction and KG-based question answering tasks. |
Label-Free Distant Supervision for Relation Extraction via Knowledge Graph Embedding (D18-1)
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| Challenge: | Existing methods to generate large scale labeled data for relation extraction produce noisy relation labels when there are multiple relationships between entities. |
| Approach: | They propose a method which assumes that a pair of entities appears in a Knowledge Graph and trains a relation classifier. |
| Outcome: | The proposed method performs well in the current distant supervision dataset. |