Papers by Shi Mingcong
Multi-Granularity History and Entity Similarity Learning for Temporal Knowledge Graph Reasoning (2024.emnlp-main)
Copied to clipboard
| Challenge: | Existing models for Temporal Knowledge Graph reasoning capture repetitive history, ignoring the entity's multi-hop neighbour history which can provide valuable background knowledge for TKG reasoning. |
| Approach: | They propose a multi-granularity history and entity similarity learning model which captures the similarity between entities. |
| Outcome: | The proposed model can predict unknown facts based on historical information, but most existing models ignore multi-hop neighbour history which can provide valuable background knowledge for TKG reasoning. |