Papers with Few-shot knowledge graph completion
P-INT: A Path-based Interaction Model for Few-shot Knowledge Graph Completion (2021.findings-emnlp)
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| Challenge: | Existing methods to encode and match entity pairs have only a few observed reference entity pairs. |
| Approach: | They propose a model that infers and leverages paths that can expressively encode the relation of two entities. |
| Outcome: | The proposed model outperforms the state-of-the-art models by 11.2– 14.2% in terms of Hits@1. |
Data Augmentation for Few-Shot Knowledge Graph Completion from Hierarchical Perspective (2022.coling-1)
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| Challenge: | Existing knowledge graph completion models require only a few associative triples to complete a relationship. |
| Approach: | They propose to perform data augmentation from two perspectives to solve the FKGC problem by inferring new triple facts from existing models. |
| Outcome: | The proposed framework can be applied to a number of existing models. |
Learning Inter-Entity-Interaction for Few-Shot Knowledge Graph Completion (2022.emnlp-main)
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| Challenge: | Recent FKGC studies focus on learning semantic representations of entity pairs by separately encoding the neighborhoods of head and tail entities. |
| Approach: | They propose a model to learn semantic representations of entity pairs by separately encoding the neighborhoods of head and tail entities. |
| Outcome: | The proposed model outperforms state-of-the-art methods on two public datasets. |