Supervised Gradual Machine Learning for Aspect-Term Sentiment Analysis (2023.tacl-1)
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| Challenge: | Recent work shows that Aspect-Term Sentiment Analysis (ATSA) can be performed by Gradual Machine Learning (GML) but the current unsupervised solution is limited by inaccurate knowledge conveyance. |
| Approach: | They propose a supervised approach which leverages binary polarity relations between instances to enable supervised knowledge conveyance. |
| Outcome: | The proposed approach outperforms pure DNN solutions on real benchmark data. |
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