Papers by Minh Dinh
Prompted Aspect Key Point Analysis for Quantitative Review Summarization (2024.acl-long)
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| Challenge: | Recent abstractive approaches generate KPs based on sentences, resulting in overlapping and hallucinated opinions. |
| Approach: | They propose to use supervised learning to extract short sentences as key points before matching them to review comments for quantification of KP prevalence. |
| Outcome: | The proposed framework achieves state-of-the-art performance on Yelp and SPACE. |
Aspect-based Key Point Analysis for Quantitative Summarization of Reviews (2024.findings-eacl)
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| Challenge: | Existing studies on review summarization use only major opinions, but ignore minority opinions and fail to quantify opinion prevalence. |
| Approach: | They propose a framework for quantitative review summarization using aspect-based key point analysis (ABKPA) they use aspect-basic sentiment analysis to automatically annotate silver labels for matching aspect-sentiment pairs . |
| Outcome: | The proposed framework outperforms state-of-the-art baselines on Yelp reviews on five business categories. |