Cross-Domain Sentiment Classification using Semantic Representation (2022.findings-emnlp)
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| Challenge: | Existing studies on cross-domain sentiment classification ignore the semantic relevance between domains. |
| Approach: | They propose to use Abstract Meaning Representation to help with cross-domain sentiment classification by combining sentence-level AMRs with text-graph interaction models. |
| Outcome: | The proposed model is effective over strong baselines and shows its importance over strong models. |
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