Documents Representation via Generalized Coupled Tensor Chain with the Rotation Group constraint (2021.findings-acl)
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| Challenge: | despite the diversity of linguistic structures, vector embedding models lack order-preserving properties . current methods for learning linguistic structure can be expensive and time-consuming . |
| Approach: | They propose a method for embedding documents and words in rotation group . they capture word order and higher-order word interactions . |
| Outcome: | The proposed model achieves the best results in document classification benchmarks. |
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