Relation-Aware Collaborative Learning for Unified Aspect-Based Sentiment Analysis (2020.acl-main)
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| Challenge: | Existing studies focus on one of three subtasks for aspect-based sentiment analysis (ABSA) Existing work develops separate methods for each subtask, or takes OE as an auxiliary task of AE. |
| Approach: | They propose a relation-aware collaborative learning framework which allows subtasks to work coordinately via multi-task learning and relation propagation mechanisms. |
| Outcome: | Extensive experiments on three real-world datasets show that RACL outperforms state-of-the-art methods for ABSA. |
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| Challenge: | Aspect terms and opinion terms are key problems of fine-grained aspect-based sentiment analysis. |
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| Challenge: | Existing work on Aspect-based sentiment analysis ignores the rich label semantics of ABSA. |
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