Papers by Wei-Shinn Ku
A Localized Geometric Method to Match Knowledge in Low-dimensional Hyperbolic Space (2022.emnlp-main)
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| Challenge: | Existing methods for entity alignment are limited to Euclidean space and hyperbolic embedding can represent hierarchical structure in knowledge graphs. |
| Approach: | They propose a localized geometric method to find equivalent entities in hyperbolic space using a hyperbolical neural network. |
| Outcome: | The proposed method outperforms the state-of-the-art by a large margin. |